Machine Learning Engineer

🏢 Summary: Full-cycle Recruiter role focused on hiring across multiple departments in a fast-paced, high-growth environment. The position involves sourcing, screening, coordinating interviews, managing ATS data, and leveraging AI tools to improve recruiting efficiency and hiring outcomes. The role offers competitive compensation, hybrid work, comprehensive benefits, and professional development opportunities. 🗂️ Requirements: Bachelor's degree or equivalent professional experience, 2–4 years of full-cycle recruiting experience, Experience in fast-paced agency, startup, or high-growth environments, Experience recruiting for marketing, creative, product, or technology roles, Proficiency with ATS platforms, Proficiency with LinkedIn Recruiter, Proficiency with Google Workspace, Experience using AI tools for sourcing and recruiting efficiency, Ability to manage multiple searches simultaneously, Strong stakeholder management and communication skills, Ability to work independently in collaborative environments, Problem-solving and adaptability skills 📃 Skills: ATS, LinkedIn, Google, ChatGPT, Gemini, Claude, Excel 🏢 Description: About the Role As a Recruiter, you will play a key role in attracting and hiring exceptional talent across the organization. You will own full-cycle recruitment for a variety of roles, partnering closely with hiring managers to develop effective hiring strategies and deliver an outstanding candidate experience. You will also contribute to improving our recruiting processes, strengthening our talent pipelines, and leveraging AI and technology to drive faster, smarter hiring decisions in a fast-paced, high-growth environment. Responsibilities include, but are not limited to: Own and execute full-cycle recruitment across multiple departments, from intake meetings through offer acceptance. Partner with hiring managers to understand hiring needs, define candidate profiles, and develop effective recruiting strategies. Source, engage, and attract top active and passive talent using LinkedIn Recruiter, job boards, referrals, networking, and other creative sourcing techniques. Conduct recruiter screens to evaluate candidate experience, technical qualifications, and overall fit. Guide candidates through the interview process while delivering an exceptional candidate experience from initial outreach through onboarding. Coordinate interviews and manage communication between candidates, hiring managers, and interview panels. Partner with hiring managers throughout the hiring process, providing recruiting best practices, market insights, and candidate recommendations. Build and maintain strong talent pipelines for current and future hiring needs. Maintain accurate candidate records, interview feedback, and recruiting data within the Applicant Tracking System (ATS). Leverage AI tools and emerging technologies to improve sourcing, candidate outreach, interview preparation, market research, process documentation, and overall recruiting efficiency while maintaining high standards of quality and accuracy. Research new sourcing strategies, recruiting platforms, and market trends to continuously improve hiring outcomes. Track recruiting metrics and provide regular hiring updates to stakeholders. Collaborate with HR, Finance, Legal, and other cross-functional teams to ensure a smooth hiring and onboarding process. Represent the company and employer brand professionally throughout every stage of the recruitment process. Support continuous improvement of recruiting processes, documentation, and interview practices. Requirements Bachelor's degree in Human Resources, Business Administration, Marketing, or a related field, or equivalent professional experience. 2–4 years of full-cycle recruiting experience, preferably in a fast-paced agency, startup, or high-growth environment. Experience recruiting for marketing, digital marketing, creative, product, or technology roles is strongly preferred. Proficiency with Applicant Tracking Systems (ATS), LinkedIn Recruiter, Google Workspace, and other recruiting technologies. Strong AI user, with experience leveraging tools such as ChatGPT, Gemini, Claude, or similar AI platforms to improve sourcing, research, communication, and recruiting efficiency. Excellent communication, organization, and stakeholder management skills, with the ability to manage multiple searches simultaneously. Ability to build strong relationships with candidates and hiring managers while maintaining confidentiality and professionalism. Demonstrated ability to prioritize effectively, work independently, and thrive in a fast-paced, collaborative environment. Strong "Figure It Out" mentality—resourceful, proactive, adaptable, and comfortable solving problems with minimal direction. Our interview process includes, but is not limited to the following: Excel and Typing Test We offer a competitive salary and benefits based on education, experience, and skills level, including: Unlimited vacation policy Monthly Phone Stipend Comprehensive Medical, Dental, and Vision insurance options 401(K) plan with matching Dog friendly office Hybrid work opportunity Professional Development Program Seamless allowance Base salary based on education, experience, and skills level ($70,200-$162,800) Level 1 - Possesses essential capabilities. $70,200-$88,720 Level 2 - Possesses developing capabilities. $88,720-$107,240 Level 3 - Possesses notable capabilities. $107,240-$125,760 Level 4 - Possesses strong capabilities. $125,760 -$144,280 Level 5 - Possesses advanced capabilities. $144,280-$162,800 About WITHIN WITHIN is the world's first Performance Branding company, partnering with some of the biggest brands in the world to drive business growth through innovative marketing strategies. Our integrated operating model collapses the traditional marketing silos between creative and media, performance and brand, and across media channels. With a full suite of offerings including media, creative, SEO, Lifecycle, Retail Media, Affiliate and Influencer, we're able to work with our brand partners in an integrated fashion, allowing us to align marketing strategies back to core business objectives. Client teams at WITHIN are trained on how to always act as a trusted business partner, acting as a fiduciary to client needs above our own. Teams at WITHIN have the ability to work with iconic brands such as The North Face, Timberland, Ben and Jerry's and Jose Cuervo. Everyone at WITHIN wants to grow and be challenged. It's a collaborative place made up of small, closely knit and versatile teams that are fast and adaptive to solve problems and build systems. Check out some of our work! We weave AI into everything we do, using the latest tech across all teams to innovate, work smarter, and make better decisions. Whether it's in creative, operations, or anything else, AI helps us level up and do things at a whole new scale. We expect our people to use AI in their daily work, fully embracing it as a critical tool to help us succeed. Join Our Network! Stay connected with us and be the first to know about new opportunities, industry insights, and updates. Follow us on: LinkedIn WhatsApp Community Instagram Tik Tok Locations New York City: 43-01 22nd St, Suite 602, Queens, NY 11101, United States Bogotá: WeWork Av. Carrera 19 #100-45 Usaquén, Piso (Floor) 10, Bogotá, Distrito Capital de Bogotá 110111, Colombia Mexico City: Av. Insurgentes Sur 1082, Piso (Floor) 2, Oficina 2008, Ciudad de México, CDMX 03100, México AI-Assisted Screening Notice As part of our initial application review process, we may use an AI-assisted tool to help compare skills and job titles from your resume with the requirements of the role. This tool evaluates information based on contextual relevance and is used only to support our manual review process. It is not used to make hiring decisions. If you are a resident of New York City and would like to request an alternative evaluation process or a reasonable accommodation, please contact us at 315-533-2388.

🏢 Summary: Senior Machine Learning Engineer role focused on building and scaling end-to-end recommendation systems for personalized content and workout experiences. The position involves developing real-time ML services, running experiments, and deploying production-grade models in a cloud-based environment. You will contribute to unified recommendation architecture and LLM-driven personalization initiatives. 🗂️ Requirements: 4+ years of experience in machine learning, Experience in recommender systems or applied ML domains, Degree in Computer Science, Machine Learning, Statistics, Mathematics or related quantitative field, Hands-on experience building, training and evaluating ML models, Strong software engineering skills, Professional experience with Python, Experience with large-scale data pipelines, Experience with distributed data processing, Experience with Spark and Airflow, Experience with AWS or similar cloud environment, Experience with Kubernetes and production serving technologies, Experience with A/B testing and experiment analysis 📃 Skills: Python, Spark, Airflow, AWS, S3, Kubernetes, RecommenderSystems, DeepLearning, Transformers, LLMs, MLOps, REST, gRPC, FastAPI, ABTesting 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Machine Learning Engineer to join the Personalization team, which owns the recommendation systems powering content discovery across the ecosystem. In this role, you will work on end-to-end ML systems: building and training models, improving real-time recommendation services, running experiments, and deploying scalable solutions into production. You will help evolve the recommendation platform from multiple models toward a more unified, real-time architecture, while also contributing to company's IQ initiatives involving LLMs, personalized plans, and AI-powered member experiences. Key takeaways: Stack : Python, Spark, Airflow, AWS, S3, Kubernetes, recommender systems, Deep Learning, Transformers, LLMs, MLOps, REST/gRPC/FastAPI, A/B testing Salary : 31 000 PLN - 35 000 PLN gross on the Contract of Employment Working model : Hybrid - 3 days/week from the office Location : ul. Grzybowska 60, Warsaw Recruitment process : A call with MOTIFE Recruiter Hiring Manager screening Coding interview Panel interviews with the team (coding, architecture, and cross-collaboration interviews, Hiring Manager meeting) Responsibilities: Build, train, evaluate, and improve ML models powering personalized workout and content recommendations. Develop and maintain data and ML pipelines using Python, Spark, Airflow, AWS, and S3. Productionize, deploy, monitor, and optimize ML models and recommendation services. Improve real-time model serving, including latency, scalability, reliability, and infrastructure costs. Support the evolution of recommendation systems toward unified rankers, candidate generation, and inference services. Run A/B tests and analyze experiment results with Product Analysts to measure product and member impact. Contribute to IQ initiatives, including personalized plans, insights, LLM-based features, and responsible AI practices. Collaborate with ML Engineers, Data Engineers, Software Engineers, Platform Engineers, Product Managers, and Analysts to deliver scalable personalization features. Requirements: 4+ years of experience in machine learning, ideally in recommender systems, NLP, computer vision, or another applied ML domain. Degree in Computer Science, Machine Learning, Statistics, Mathematics, Operational Research, or another quantitative field. Strong hands-on experience building, training, evaluating, and improving ML models. Solid software engineering skills, including clean code, data structures, algorithms, and production readiness. Professional experience with Python; experience with Java, Kotlin, Go, C, or C++ is a plus. Experience with large-scale data pipelines, distributed processing, and orchestration tools such as Spark and Airflow. Familiarity with cloud-based ML environments, preferably AWS, and production serving technologies such as Kubernetes, REST, gRPC, or FastAPI. Strong communication skills and the ability to work cross-functionally with product, analytics, platform, data, and engineering teams. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If this sounds like your next step, we’d love to hear from you! Please apply via our careers page and submit your CV in English.

🏢 Summary: Distinguished Machine Learning Engineer role within the Autonomy Behaviors team focused on developing and deploying deep learning solutions for prediction, planning, and control in autonomous vehicles. The position involves leading large-scale ML experimentation, building production-grade models, and collaborating cross-functionally to deliver industrial-strength systems. Candidates must bring extensive experience in autonomous vehicle ML systems, deep neural networks, and large-scale model deployment. 🗂️ Requirements: BS/MS/PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Applied Math or related field, 15+ years of experience building ML systems for autonomous vehicles or similar robotics applications, Deep understanding of large language models (LLM) and transformers, Hands-on experience building and deploying large-scale production ML systems, Experience training, optimizing, and deploying deep neural networks in PyTorch, TensorFlow, or TensorRT, Strong mathematical foundation in machine learning and deep learning, Proven leadership and innovation in ML-based planning solutions 📃 Skills: Python, MachineLearning, DeepLearning, LLM, Transformers, DNN, PyTorch, TensorFlow, TensorRT, Prediction, Planning, Control, Optimization 🏢 Description: Motional is seeking a distinguished Machine Learning Engineer to join its Autonomy team in Behaviors. As a member of our team you will develop key features for our autonomous driving platform. In this role, you will apply machine learning to a mix of prediction, planning, and control problems. The candidate is required to have hands-on experience and deep knowledge in machine learning. Understanding of deep neural networks, autonomous vehicles, and domain adaptation is highly desirable. You should have strong research, SW development, communication, interpersonal, and analytical skills. What you'll be doing: - Researching, implementing, and evaluating deep-learning-based methods for prediction and planning for Autonomous Vehicle products. - Leading, designing, running, and analyzing experiments and testing to evaluate the efficiency of solutions on real-world data. - Partnering with system software engineering specialists to ship industrial strength ML models. - Communicating and collaborating with multi-functional teams. What We're Looking For: - BS/MS/PhD in computer science, electrical engineering, mechanical engineering, applied math, or related fields (or equivalent experience) - 15+ years of proven experience building ML systems for autonomous vehicles or similar robotics applications - Deep understanding of large language models (LLM) and transformers - Hands on experience building large scale production ML systems and deploying them at scale - Excellent leadership and track record for innovation to help build the next generation of ML based planning solutions - Experience with deep neural network (DNN) training, inference and optimization in leading frameworks (Pytorch, Tensorflow, TensorRT, etc.) - Excellent understanding of the mathematical foundations of machine learning and deep learning Bonus Points: - Prior experience as a ML planning lead - Proven publication record in ML for planning, vision, or related fields - Prior experience building and deploying vision language action or chain of thought models Salary Range $271,000—$373,000 USD The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. Benefits: Candidates for certain positions are eligible to participate in the benefits program, including but not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.

🏢 Summary: Machine Learning Engineer role focused on building statistical models and production systems for mobile ad tech economics, optimization, and advertiser performance. The position involves experimentation, bidding innovation, and collaboration across engineering and business teams in a remote-first environment. 🗂️ Requirements: PhD in Computer Science, Machine Learning, Economics, or related field, Industry experience applying economics or machine learning at large scale, Solid engineering and coding skills, Excellent communication and collaboration skills 📃 Skills: Python, MachineLearning, Statistics, Economics, Optimization, Experimentation, AdTech, Modeling, Coding 🏢 Description: About the Revenue Engine team The Revenue Engine team works to understand the fundamental economics of the mobile ad tech marketplace, including the elasticity of demand and the effects of competition. The team of machine learning engineers, software engineers, and data analysts develops theories, validates those theories with experiments and analyses, and uses the learnings to build production systems that improve outcomes for advertisers. As a Machine Learning Engineer on the Revenue Engine team, you will: - Build statistical models and production systems to balance advertiser performance with business goals. - Tune optimization parameters, measure internal competition, and model dynamic environments. - Design and run experiments to validate theories underpinning the mobile ad tech economy. - Develop applications in the areas of advertiser budget retention and growth, optimal margin allocation, and bidding innovations. - Collaborate with engineers and peers across Operations and GTM teams. - Use strong communication skills to explain statistical and machine learning concepts to technical and non-technical audiences. - Contribute to an engineering excellence culture through state-of-the-art tools, risk-driven testing, explainable systems, and design/code review. Requirements: - PhD in Computer Science, Machine Learning, Economics, or a related field. - Industry experience applying economics or machine learning to large scale problems. - Solid engineering and coding skills. - Excellent team communication and collaboration skills. - Experience with ad tech is a plus. Location: The preferred location for this role is within California. The company is remote-first with US hubs in Redwood City, Los Angeles, and New York City. Travel Expectations: Employees are expected to attend in-person gatherings, including project meetings, regional meetups, and company-wide events, at least once per quarter. Compensation: The compensation package includes equity and health, vision, and dental benefits associated with the employee's country of residence. Base compensation varies by location and experience. Base salary ranges: - SF Bay Area, Los Angeles/Orange County, NYC, Seattle: $235,000 - $275,000 - All other approved states: $215,000 - $255,000 Benefits may include medical coverage, wellness stipends, and additional perks based on country of residence.

🏢 Summary: The role focuses on building and operating scalable, low-latency machine learning infrastructure for real-time personalization services. You will design and maintain Python-based microservices, deploy ML models to cloud environments, and ensure high availability and performance of recommendation systems. The position involves close collaboration with ML and platform teams to bring ML-powered features into production. 🗂️ Requirements: 3+ years of professional software engineering experience, Degree in Computer Science, Engineering, or related technical field, Strong knowledge of data structures and algorithms, Professional experience building backend services in Python, Experience designing RESTful APIs or gRPC services, Experience building microservices architectures, Experience deploying production services on AWS, GCP, or Azure, Experience with relational and non-relational databases, Experience with event-driven architectures and message queues, Strong debugging, profiling, and performance tuning skills 📃 Skills: Python, AWS, GCP, Azure, Kubernetes, Docker, REST, gRPC, Kafka, RabbitMQ, SQS, Postgres, MySQL, DynamoDB, Redis, CI/CD, Terraform, Datadog, Grafana, MLflow 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Machine Learning Infrastructure Engineer to join the Personalization team, which owns the systems powering content recommendations across the company’s digital ecosystem. In this role, you will design, build, and maintain low-latency, highly scalable services that make real-time personalization possible. You will work hands-on with backend services, cloud infrastructure, model serving, observability, and performance optimization, partnering closely with ML Engineers, API Engineers, Platform Engineers, and Product Managers to bring ML-powered product features into production. Key takeaways: Stack : Python, AWS/GCP/Azure, Kubernetes, Docker, REST, gRPC, Kafka/RabbitMQ/SQS, Postgres, MySQL, DynamoDB, Redis, CI/CD, Terraform, Datadog/Grafana/MLflow Salary : 24 000 PLN - 28 000 PLN gross on the Contract of Employment Working model : Hybrid - 3 days/week from the office Location : ul. Grzybowska 60, Warsaw Recruitment process : A call with MOTIFE Recruiter Hiring Manager screening Coding interview Panel interviews with the team (coding, architecture, and cross-collaboration interviews, Hiring Manager meeting) Responsibilities: Design, build, and maintain Python microservices powering personalized content recommendations. Productionize, deploy, monitor, and operate machine learning services in cloud-based production environments. Partner with ML Engineers to integrate models into scalable backend services and real-time recommendation workflows. Ensure high availability, low latency, and strong performance through caching, load balancing, auto-scaling, and capacity planning. Own and improve personalization services, including reliability, testability, observability, scalability, and operational readiness. Conduct performance tuning, profiling, and latency optimization for high-traffic recommendation workloads. Collaborate with platform teams to use infrastructure, tooling, and deployment workflows that support fast product iteration. Work with Product Managers, ML Engineers, API Engineers, and Data Engineers to launch ML-powered personalization features. Requirements: 3+ years of professional software engineering experience and a degree in Computer Science, Engineering, or a related technical field. Strong software engineering fundamentals, including data structures, algorithms, clean code, testing, and reproducibility. Professional experience building backend services in Python; experience with Java, Kotlin, Go, C, or C++ is welcome. Experience designing and building RESTful APIs, gRPC services, or microservices from the ground up. Strong experience deploying and managing production services on AWS or GCP, or Azure. Experience with relational and non-relational databases such as Postgres, MySQL, DynamoDB, or Redis. Experience with event-driven architectures and message queues such as Kafka, RabbitMQ, or SQS. Strong debugging, profiling, and performance tuning skills, including latency tracking, scalability analysis, and production troubleshooting. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If this sounds like your next step, we’d love to hear from you! Please apply via our careers page and submit your CV in English.

🏢 Summary: The role involves building and operating scalable, low-latency machine learning infrastructure to power real-time personalization and content recommendations. You will design and maintain Python-based microservices, deploy ML models to cloud environments, and ensure high availability and performance of production systems. The position focuses on backend engineering, cloud infrastructure, and model serving within a cross-functional ML product team. 🗂️ Requirements: 3+ years of professional software engineering experience, Degree in Computer Science, Engineering, or related technical field, Strong knowledge of data structures and algorithms, Professional experience building backend services in Python, Experience designing RESTful APIs or gRPC services, Experience building microservices architectures, Experience deploying production services on AWS, GCP, or Azure, Experience with relational and non-relational databases, Experience with event-driven architectures and message queues, Strong debugging, profiling, and performance tuning skills 📃 Skills: Python, AWS, GCP, Azure, Kubernetes, Docker, REST, gRPC, Kafka, RabbitMQ, SQS, Postgres, MySQL, DynamoDB, Redis, CI/CD, Terraform, Datadog, Grafana, MLflow 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Machine Learning Infrastructure Engineer to join the Personalization team, which owns the systems powering content recommendations across the company’s digital ecosystem. In this role, you will design, build, and maintain low-latency, highly scalable services that make real-time personalization possible. You will work hands-on with backend services, cloud infrastructure, model serving, observability, and performance optimization, partnering closely with ML Engineers, API Engineers, Platform Engineers, and Product Managers to bring ML-powered product features into production. Key takeaways: Stack : Python, AWS/GCP/Azure, Kubernetes, Docker, REST, gRPC, Kafka/RabbitMQ/SQS, Postgres, MySQL, DynamoDB, Redis, CI/CD, Terraform, Datadog/Grafana/MLflow Salary : 24 000 PLN - 28 000 PLN gross on the Contract of Employment Working model : Hybrid - 3 days/week from the office Location : ul. Grzybowska 60, Warsaw Recruitment process : A call with MOTIFE Recruiter Hiring Manager screening Coding interview Panel interviews with the team (coding, architecture, and cross-collaboration interviews, Hiring Manager meeting) Responsibilities: Design, build, and maintain Python microservices powering personalized content recommendations. Productionize, deploy, monitor, and operate machine learning services in cloud-based production environments. Partner with ML Engineers to integrate models into scalable backend services and real-time recommendation workflows. Ensure high availability, low latency, and strong performance through caching, load balancing, auto-scaling, and capacity planning. Own and improve personalization services, including reliability, testability, observability, scalability, and operational readiness. Conduct performance tuning, profiling, and latency optimization for high-traffic recommendation workloads. Collaborate with platform teams to use infrastructure, tooling, and deployment workflows that support fast product iteration. Work with Product Managers, ML Engineers, API Engineers, and Data Engineers to launch ML-powered personalization features. Requirements: 3+ years of professional software engineering experience and a degree in Computer Science, Engineering, or a related technical field. Strong software engineering fundamentals, including data structures, algorithms, clean code, testing, and reproducibility. Professional experience building backend services in Python; experience with Java, Kotlin, Go, C, or C++ is welcome. Experience designing and building RESTful APIs, gRPC services, or microservices from the ground up. Strong experience deploying and managing production services on AWS or GCP, or Azure. Experience with relational and non-relational databases such as Postgres, MySQL, DynamoDB, or Redis. Experience with event-driven architectures and message queues such as Kafka, RabbitMQ, or SQS. Strong debugging, profiling, and performance tuning skills, including latency tracking, scalability analysis, and production troubleshooting. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If this sounds like your next step, we’d love to hear from you! Please apply via our careers page and submit your CV in English.

🏢 Summary: Senior Backend Engineer role to architect and build the core systems of a next-generation AdTech platform, focusing on high-throughput, low-latency services for campaign delivery, targeting, and attribution. The position involves defining system architecture from the ground up using Python, Django, Kubernetes, and AWS in a distributed, scalable environment. Engineers will drive technical direction, optimize performance, and provide leadership in a fast-paced, product-driven setting. 🗂️ Requirements: 5+ years of software development experience building scalable backend systems, Strong knowledge of algorithms, data structures, networking, and databases, Proven experience designing and scaling distributed systems, Experience with backend programming languages (e.g. Java, .NET, Python, Node.js), Ability to design high-throughput, low-latency systems, Experience with system architecture and technical decision-making, Availability to work until 1pm EST, Upper-intermediate English level 📃 Skills: Python, Django, Kubernetes, AWS, PostgreSQL, Java, .NET, Node.js, ETL, OpenRTB, Prebid.js, GoogleAdManager, AmazonUAM, DSP, SSP 🏢 Description: ID68432 AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards. Why join us If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! :) About the role We are looking for a Senior Backend Engineer to architect and build the core systems of a next-generation AdTech platform that embeds products directly into visual experiences. You will design high-throughput, low-latency services for campaign delivery, targeting, attribution, and partner integrations using Python, Django, Kubernetes, and AWS. This is an early-stage initiative where senior engineers define the technical direction and system architecture from the ground up. What you will do Architect, build, and evolve core systems for the Ads platform; Design APIs and services supporting campaign management, targeting, delivery, attribution, and reporting; Build and optimize high-throughput, low-latency systems processing large volumes of events and data; Own critical systems end-to-end, including design, implementation, deployment, monitoring, and ongoing improvements; Drive architectural decisions and establish patterns that support scalability, reliability, and developer productivity; Collaborate closely with product, data, and partner teams to translate business requirements into robust technical solutions; Provide technical leadership through design reviews, system discussions, and mentoring other engineers; Contribute to engineering best practices, documentation, and long-term platform vision; Participate in hiring and help grow a strong, high-performing team. Must haves 5 years of software development experience building scalable systems using backend programming languages/frameworks (e.g. Java , .NET , Python , Node.js , etc); Deep understanding of computer science fundamentals, including algorithms, data structures, networking, and databases; Proven experience designing and scaling distributed systems with a focus on performance, observability, and fault tolerance; Strong architectural instincts and the ability to make high-leverage technical decisions that impact multiple teams and systems; Demonstrated ability to influence and mentor senior engineers, guide teams through ambiguity, and elevate engineering practices across the board; Exceptional ownership mindset; Availability to work till 1pm EST (till 8 pm Kyiv time) ; Excellent communication and cross-functional collaboration skills; Comfortable operating in a fast-paced, high-autonomy, product-driven environment; Experience with e-commerce and catalog management is preferred; Familiarity with Python , Django , Kubernetes , PostgreSQL , and AWS is strongly preferred, but deep expertise in analogous systems and a willingness to learn are welcome; Upper-intermediate English level. Nice to haves Strong experience with complex ETL flows and high-throughput systems is highly preferred; Experience with AdTech (This may include experience with DSPs, SSPs, ad exchanges, affiliate programs, Prebid.js, Prebid Server, Google Ad Manager, Amazon UAM/TAM, OpenRTB, identity and addressability solutions, as well as ad operations workflows.) The benefits of joining us Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive. Meet Our Recruitment Process Asynchronous stage – An automated, self-paced track that helps us move faster and give you quicker feedback: Short online form to confirm basic requirements 30–60 minute skills assessment via Codility – a platform founded in Poland that helps us provide quicker feedback and streamline this stage of the process. 5-minute introduction video Synchronous stage – Live interviews Technical interview with our engineering team (scheduled at your convenience) Final interview with your future teammates If it’s a match — you’ll get an offer!

🏢 Summary: Senior Backend Engineer role focused on architecting and building the core systems of a next-generation AdTech platform, designing high-throughput, low-latency services for campaign delivery, targeting, and attribution. The position involves defining system architecture from scratch, scaling distributed systems, and providing technical leadership in a fast-paced environment. Strong experience with scalable backend development and AdTech ecosystems is required. 🗂️ Requirements: 5+ years of experience building scalable backend systems, Experience in AdTech (DSPs, SSPs, ad exchanges, Prebid, Google Ad Manager, OpenRTB, etc.), Strong knowledge of algorithms, data structures, networking, and databases, Proven experience designing and scaling distributed systems, Experience with backend programming languages (Java, .NET, Python, Node.js), Ability to design high-throughput, low-latency systems, Upper-intermediate English level, Availability to work until 1pm EST, Experience mentoring engineers and driving architectural decisions 📃 Skills: Python, Django, Kubernetes, AWS, PostgreSQL, Java, .NET, Node.js, OpenRTB, Prebid.js, Prebid, GoogleAdManager, AmazonUAM, AmazonTAM, ETL 🏢 Description: ID52365 AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards. Why join us If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! :) About the role We are looking for a Senior Backend Engineer to architect and build the core systems of a next-generation AdTech platform that embeds products directly into visual experiences. You will design high-throughput, low-latency services for campaign delivery, targeting, attribution, and partner integrations using Python, Django, Kubernetes, and AWS. This is an early-stage initiative where senior engineers define the technical direction and system architecture from the ground up. What you will do Architect, build, and evolve core systems for the Ads platform; Design APIs and services supporting campaign management, targeting, delivery, attribution, and reporting; Build and optimize high-throughput, low-latency systems processing large volumes of events and data; Own critical systems end-to-end, including design, implementation, deployment, monitoring, and ongoing improvements; Drive architectural decisions and establish patterns that support scalability, reliability, and developer productivity; Collaborate closely with product, data, and partner teams to translate business requirements into robust technical solutions; Provide technical leadership through design reviews, system discussions, and mentoring other engineers; Contribute to engineering best practices, documentation, and long-term platform vision; Participate in hiring and help grow a strong, high-performing team. Must haves 5 years of software development experience building scalable systems (backend programming languages/frameworks, e.g. Java , .NET , Python , Node.js etc); Experience with AdTech (This may include experience with DSPs, SSPs, ad exchanges, affiliate programs, Prebid.js, Prebid Server, Google Ad Manager, Amazon UAM/TAM, OpenRTB, identity and addressability solutions, as well as ad operations workflows); Deep understanding of computer science fundamentals (algorithms, data structures, networking, databases); Proven experience designing and scaling distributed systems focusing on performance, observability, and fault tolerance; Strong architectural instincts and the ability to make high-leverage technical decisions that impact multiple teams and systems; Demonstrated ability to influence and mentor senior engineers, guide teams through ambiguity, and elevate engineering practices across the board; Exceptional ownership mindset — you drive initiatives forward, raise the bar, and deliver lasting impact; Excellent communication and cross-functional collaboration skills; Availability to work till 1pm EST (till 8 pm Kyiv time) ; Comfortable operating in a fast-paced, high-autonomy, product-driven environment; Experience with e-commerce and catalog management is preferred; Familiarity with Python , Django , Kubernetes , PostgreSQL , and AWS is strongly preferred, but deep expertise in analogous systems and a willingness to learn are welcome; Upper-intermediate English level. Nice to haves Strong experience with complex ETL flows and high-throughput systems is highly preferred. The benefits of joining us Professional growth Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps Competitive compensation We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities A selection of exciting projects Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands Flextime Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive. Meet Our Recruitment Process Asynchronous stage – An automated, self-paced track that helps us move faster and give you quicker feedback: Short online form to confirm basic requirements 30–60 minute skills assessment via Codility – a platform founded in Poland that helps us provide quicker feedback and streamline this stage of the process. 5-minute introduction video Synchronous stage – Live interviews Technical interview with our engineering team (scheduled at your convenience) Final interview with your future teammates If it’s a match — you’ll get an offer!

🏢 Summary: Analytics Engineer role focused on building scalable healthcare data products and analytics-ready datasets for PBM and care navigation operations. The position involves developing dbt-based data models, optimizing cloud data platforms, implementing data quality frameworks, and enabling AI-assisted analytics capabilities. Candidates will collaborate cross-functionally to deliver reliable, maintainable, and auditable data solutions in a modern analytics environment. 🗂️ Requirements: 3+ years experience in analytics engineering, data modeling, data warehousing or related field, Strong experience with dbt, Advanced SQL proficiency, Experience developing data transformations and workflows using Python, Understanding of dimensional modeling and scalable data architecture, Experience building production-grade data models and data quality tests, Experience with cloud data warehouses, Experience orchestrating and monitoring data pipelines, Experience working in cloud environments, Familiarity with Git and CI/CD workflows, Knowledge of testing and deployment workflows, Strong problem-solving and analytical skills, Ability to collaborate with technical and non-technical stakeholders 📃 Skills: dbt, SQL, Python, Redshift, Snowflake, BigQuery, Airflow, Dagster, AWS, Git, CI/CD, MCP, Claude 🏢 Description: ABOUT THE ROLE: We are seeking an Analytics Engineer to join our Analytics Platform team to design, build and maintain scalable data products that power our Pharmacy Benefit Management (PBM) and Care Navigation organizations. In this role, you will be responsible for transforming complex healthcare data into trusted, analytics ready datasets that support operational reporting, client insights, financial analysis and strategic decision-making. You will partner closely with Analytics, Data Engineering, Clinical, Client Success, Product and Operations teams to build reliable and scalable data models within our data foundry. This role is ideal for someone who is passionate about analytics engineering, has strong dbt expertise, enjoys solving complex healthcare data challenges and thinks beyond individual requests to build reusable and maintainable systems. You will play a key role in shaping the future of our data platform by developing high-quality data products, establishing engineering best practices, and helping the organization evolve toward AI-enabled and self-service analytics capabilities. WHAT YOU'LL DO: • Apply hands on analytics and data expertise to solve complex, fast moving financial and operational problems in the health tech space • Design, develop and maintain scalable, analytics ready data models (primarily in dbt) that power a PBM and care navigation data ecosystem that support client reporting, performance analytics, operational analysis and self-service business intelligence • Translate complex pharmacy benefits and healthcare navigation workflows, business rules and operational processes into transparent, maintainable, and auditable data models • Partner closely with data and analytics engineers, data analysts and business stakeholders to deliver reliable data products that can be leveraged across multiple use cases and continuously optimize data models and warehouse performance to support large-scale PBM/care navigation datasets and growing business needs • Implement automated data quality checks, testing frameworks and reconciliation processes to ensure data reliability • Establish documentation standards, lineage and analytics engineering guardrails that promote transparency and auditability • Contribute to engineering best practices including version control, CI/CD, incremental models, code reviews, and observability • Contribute to data governance by establishing modeling standards, documentation and guardrails that support auditability, explainability and long term maintainability • Build data foundations that enable future agentic analytics engineering use cases, including self-service analytics and AI-assisted insight generation • Stay informed on emerging technologies and identify opportunities to incorporate AI into analytics engineering workflows WHO YOU ARE: • 3+ years of experience in analytics engineering, data modeling, data warehousing or a related field • Strong experience with dbt and modern analytics engineering best practices (required) • Advanced SQL proficiency and experience developing data transformations and workflows using python • Strong understanding of dimensional modeling, medallion architecture, semantic modeling and scalable data architecture principles • Experience building and maintaining production-grade data models, data quality tests, and documentation • Experience working with cloud data warehouses such as Amazon Redshift, Snowflake, or BigQuery • Experience orchestrating and monitoring data pipelines using tools such as Apache Airflow, Dagster etc. • Experience working within cloud environments, preferably AWS • Familiarity with software engineering practices including Git, CI/CD, pull request reviews, testing, and deployment workflows • Interest or experience in leveraging AI-enabled development workflows and analytics tooling, including experience with or willingness to learn technologies such as Claude, Claude Skills, Model Context Protocol (MCP) and AI assisted engineering practices • Strong problem-solving and analytical skills with a focus on building scalable, maintainable data solutions • Effective communication skills and the ability to collaborate with both technical and non-technical stakeholders COMPENSATION: $100,000 - $140,000 annually, in addition to bonus and equity. Compensation offered will be determined by geographic location, experience, and qualifications.

🏢 Summary: Senior Data Engineer role focused on building and scaling a cloud-native data platform and MLOps ecosystem, including data lakes, warehouses, and production-grade ML infrastructure. The position involves designing scalable data pipelines, operationalizing machine learning models, and implementing CI/CD for data and ML workflows in a modern cloud environment. 🗂️ Requirements: Bachelor’s or Master’s degree in Computer Science, Information Systems, or related technical field, 5+ years of experience as a Data Engineer in data and analytics environments, Strong proficiency in data modeling concepts and techniques, Hands-on experience building ETL/ELT pipelines using PySpark, Advanced Python programming skills, Advanced SQL skills including query optimization, Experience with Databricks and cloud data warehousing solutions, Experience operationalizing machine-learning models in production, Hands-on experience with ML tooling (e.g., MLflow, SageMaker, Databricks ML, Kubeflow), Experience implementing CI/CD pipelines for data and ML workflows, Experience containerizing workloads using Docker, Ability to write, test, and debug RESTful APIs, Understanding of model lifecycle management, data versioning, and feature stores, Experience with data quality initiatives such as MDM 📃 Skills: Python, SQL, PySpark, Databricks, S3, Redshift, BigQuery, MLflow, SageMaker, Kubeflow, Docker, CI/CD, REST, MDM, AWS 🏢 Description: Job Description We are looking for a Senior Data Engineer to help evolve and scale our modern data ecosystem, including our data lake, data warehouse, and machine-learning enablement platforms. This role will contribute to the company’s data-driven culture, bring innovative approaches to cloud-native engineering, and help advance our MLOps capabilities to support production-grade AI/ML initiatives. You will collaborate closely with data scientists, analytics engineers, and cross-functional partners to deliver reliable, high-quality data and operationalized machine-learning solutions. Responsibilities Designs and builds scalable data extracts, integrations, transformations, and data models. Ensures successful deployment and provisioning of data solutions across required environments. Designs and implements data architectures and applications that enable speed, quality, and operational efficiency. Interacts with cross-functional stakeholders to gather and define requirements and translate them into technical designs. Develops deep familiarity with enterprise datasets, builds domain knowledge, and advances data quality. Reviews requirements, identifies gaps, and drives resolution with stakeholders. Identifies and recommends continuous improvement opportunities, ensuring integrations are automated, governed, and observable. Serves as a key team member in designing and deploying a ground-up cloud data platform and pipeline. Partners with data scientists to design, build, and maintain reproducible machine-learning pipelines, including feature engineering, model training, validation, deployment, and monitoring. Implements CI/CD for data and ML workflows (model packaging, automated testing, environment management, release automation). Builds and maintains production-grade ML infrastructure such as feature stores, model registries, data versioning, and experiment tracking frameworks (e.g., MLflow). Ensures ML models follow best-practice governance, including automated model performance monitoring, drift detection, logging, observability, and alerting. Designs scalable data pipelines optimized for ML workloads, such as batch, streaming, and real-time inference use cases. Establishes MLOps standards, coding practices, and automation patterns that scale across teams. Qualifications Bachelor or Master`s degree in technical discipline such as Computer Science, Information Systems or another technical field People person, team player with a strong can-do mentality 5+ years of experience as a Data Engineer within a data and analytics environment. Strong interpersonal skills with a collaborative, proactive, and solution-driven mindset. Proficiency in data modeling concepts and techniques. Expertise with Databricks and other cloud data warehousing solutions such as S3, Redshift, or BigQuery. Hands-on experience building data pipelines and ETL/ELT workflows using PySpark for semi-structured data (merge, delete, combine, wrangling). Advanced knowledge of Python and advanced working SQL skills including query optimization. Ability to write, test, and debug RESTful APIs. Experience working in agile, cross-functional environments. Strong analytical, problem-solving, and critical-thinking capabilities. Ability to guide junior engineers and contribute to technical design reviews. Strong communication skills with the ability to present complex concepts clearly. Experience in data quality initiatives such as Master Data Management (MDM). Experience operationalizing machine-learning models in production environments. Hands-on experience with ML tooling such as MLflow, SageMaker, Databricks ML, Kubeflow, or similar. Experience implementing CI/CD pipelines for data and ML workloads, including automated testing, deployment pipelines, and environment configuration. Understanding of model lifecycle management, data versioning, feature store design, and model monitoring concepts. Experience containerizing ML workloads using Docker and deploying them via cloud-native services or orchestrators. Familiarity with monitoring frameworks, experiment tracking, and performance observability for ML models. Highly Desired AWS certifications (any): DevOps experience with CICD & unit/integration testing, Docker containerization, workflow orchestration Databricks certifications – Associate/Professional AWS Certified Solutions Architect – Associate/Professional AWS Certified Developer – Associate/Professional AWS Certified DevOps Engineer AWS Certified Solutions Architect AWS Certified Data Analytics AWS Certified Security - Specialty AWS Certified Cloud Practitioner #LI-JC1The anticipated pay scale for this position can be found below, however the pay range applicable to you may vary by geographic location based on where the job is located or where you work. The final pay offered to a successful candidate will be dependent on several factors that may include but are not limited to the type and years of experience within the job, the type of years and experience within the industry, education, etc. iHerb, LLC is a multi-state employer and this pay scale may not reflect positions that work in other states or locations.Employees (and their families) that meet eligibility criteria as outlined in applicable plan documents are eligible to participate in our medical, dental, vision, and basic life insurance programs and may enroll in our company’s 401(k) plan. Employees will also be eligible for Time Off and Paid Sick Leave pursuant to the company’s policies. Employees will enjoy paid holidays throughout the calendar year. Eligibility requirements for these benefits will be controlled by applicable plan documents. Hired applicant may be awarded Restrict Stock Units and receive annual bonuses pursuant to eligibility and performance criteria defined in the respective plan documents and policies. For more information on iHerb benefits, visit us at iHerbBenefits.com.Anticipated Pay Scale:$116,000—$170,000 USD Staffing Agency Submission Notice iHerb does not accept unsolicited 3rd party ("Agency") candidates. If you are an Agency, please send any requests to be considered as a supplier in our Vendor Management System to staffingvendors@iherb.com. Do not contact iHerb employees directly. If requested to work on a role, any Agency candidates would be presented through the internal recruiting organization. About iHerbiHerb is on a mission to make health and wellness accessible to all. We offer Earth’s best-curated selection of health and wellness products, at the best possible value, delivered with the most convenient experience.We’re the world’s largest eCommerce platform dedicated to vitamins, minerals, and supplements, and other health and wellness products. For more than 25 years, we’ve been making it simple for people all over the world to purchase the highest quality products. From supplements to skincare to grocery items, we ship over 50,000 products, from over 1,800 brands direct to our customers in 180+ countries.Our vision is to become the #1 destination for health and wellness across the world.With a passion for wellness and a mind for innovative solutions, iHerb team members share a vision for a healthier world that drives them each day. Our 5 Shared Values unite our global team: Focus on the Customer · Empower Our People · Be Entrepreneurial & Pivot Quickly · Embrace Diversity & Inclusion · Strive for Simplicity iHerb BenefitsAt iHerb, we are dedicated to offering programs designed to help our employees and their families stay healthy, live well, and plan for their financial future. Built on a strong foundation, our programs provide options and upgrades with flexibility, protection, and security in mind. For the comprehensive benefits list, visit www.iHerbBenefits.com. For our international team members, you may be eligible for benefits depending on the country where you are employed. The Talent Acquisition Partner/local HR representative will go over the benefits you are eligible for. iHerb is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. iHerb provides equal employment opportunities to all applicants for employment and prohibits discrimination and harassment.