Machine Learning Engineer – General ML & Generative AI

🏢 Summary: Machine Learning Engineer role focused on designing, deploying, and operating enterprise-grade classical ML and Generative AI solutions. The position involves building end-to-end ML pipelines, integrating LLM-based applications, and ensuring production stability in cloud-based environments. The role includes hybrid work, ongoing training opportunities, and a flexible benefits platform. 🗂️ Requirements: Degree in Computer Science, Data Science, Mathematics or related field, Experience delivering Generative AI solutions, Knowledge of LLM architectures and limitations, Strong Python engineering skills, Experience with Git-based version control, Experience working with CI/CD pipelines, Experience with ML and GenAI platforms, Experience with cloud environments, Fluent English, Fluent Polish, Availability for hybrid work with 1–2 office visits per week 📃 Skills: Python, Git, CI/CD, Databricks, AWS, Azure, GCP, LLM, GenAI, MachineLearning 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML as well as Generative AI, you are responsible for the technical design, implementation, and operation of enterprise-grade ML & GenAI solutions. You work in a tandem setup with an internal colleague who manages stakeholder communication and overall delivery, allowing you to concentrate on the technical realization, integration, and operational stability of ML & GenAI use cases. Design, train and optimize classical machine learning and Generative AI models for enterprise-grade use cases Build and maintain end-to-end ML and GenAI pipelines including data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of ML and GenAI solutions running in production Integrate LLM-based solutions using APIs and GenAI frameworks into existing system landscapes Collaborate closely with internal ML engineers and data teams on technical design, implementation and operational topics Benefits Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more. Language Courses – you'll have access to a multi-language learning platform enabling you to practice your language skills and learn new ones! Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development. Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions. Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Practical experience delivering Generative AI solutions and a solid understanding of LLM architectures and limitations Strong Python engineering skills, including clean code practices and software engineering best standards Hands-on experience with Git-based code versioning and working with CI/CD pipelines as a user Experience with productive ML and GenAI platforms and cloud-based environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week. About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: Machine Learning Engineer role focused on designing, deploying, and operating enterprise-grade classical ML and Generative AI solutions in hybrid cloud environments. The position involves building end-to-end ML pipelines, integrating LLM-based systems, and ensuring production stability and scalability. Candidates work closely with ML and data teams while concentrating on technical implementation and operational excellence. 🗂️ Requirements: Degree in Computer Science, Data Science, Mathematics or related field, Experience delivering Generative AI solutions, Understanding of LLM architectures and limitations, Strong Python engineering skills, Knowledge of clean code and software engineering best practices, Experience with Git-based version control, Experience working with CI/CD pipelines, Experience with ML and GenAI platforms, Experience with cloud environments, Fluent English, Fluent Polish, Availability for hybrid work with 1–2 office visits per week 📃 Skills: Python, Git, CI/CD, Databricks, AWS, Azure, GCP, LLM, GenAI, MachineLearning 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML as well as Generative AI, you are responsible for the technical design, implementation, and operation of enterprise-grade ML & GenAI solutions. You work in a tandem setup with an internal colleague who manages stakeholder communication and overall delivery, allowing you to concentrate on the technical realization, integration, and operational stability of ML & GenAI use cases. Design, train and optimize classical machine learning and Generative AI models for enterprise-grade use cases Build and maintain end-to-end ML and GenAI pipelines including data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of ML and GenAI solutions running in production Integrate LLM-based solutions using APIs and GenAI frameworks into existing system landscapes Collaborate closely with internal ML engineers and data teams on technical design, implementation and operational topics Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Practical experience delivering Generative AI solutions and a solid understanding of LLM architectures and limitations Strong Python engineering skills, including clean code practices and software engineering best standards Hands-on experience with Git-based code versioning and working with CI/CD pipelines as a user Experience with productive ML and GenAI platforms and cloud-based environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week. About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: The role focuses on designing, implementing, and operating enterprise-grade Machine Learning and Generative AI solutions, with responsibility for end-to-end pipelines and production stability. The engineer works hands-on with classical ML and LLM-based systems, ensuring robust integration into existing enterprise environments. The position emphasizes technical ownership of ML & GenAI use cases in close collaboration with internal teams. 🗂️ Requirements: University degree in Computer Science, Data Science, Mathematics or related field, Practical experience delivering Generative AI solutions, Strong understanding of LLM architectures and limitations, Strong Python engineering skills with clean code practices, Hands-on experience with Git-based version control, Experience working with CI/CD pipelines, Experience with ML and GenAI platforms in cloud environments (Databricks, AWS, Azure or GCP), Fluent English and Polish, Availability for hybrid work (1–2 office visits per week) 📃 Skills: Python, MachineLearning, GenerativeAI, LLM, Git, CICD, Databricks, AWS, Azure, GCP, APIs 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML as well as Generative AI, you are responsible for the technical design, implementation, and operation of enterprise-grade ML & GenAI solutions. You work in a tandem setup with an internal colleague who manages stakeholder communication and overall delivery, allowing you to concentrate on the technical realization, integration, and operational stability of ML & GenAI use cases. Design, train and optimize classical machine learning and Generative AI models for enterprise-grade use cases Build and maintain end-to-end ML and GenAI pipelines including data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of ML and GenAI solutions running in production Integrate LLM-based solutions using APIs and GenAI frameworks into existing system landscapes Collaborate closely with internal ML engineers and data teams on technical design, implementation and operational topics Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Practical experience delivering Generative AI solutions and a solid understanding of LLM architectures and limitations Strong Python engineering skills, including clean code practices and software engineering best standards Hands-on experience with Git-based code versioning and working with CI/CD pipelines as a user Experience with productive ML and GenAI platforms and cloud-based environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week. About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: The role focuses on designing, building, and operating production-grade machine learning solutions using classical and deep learning models. You will develop end-to-end ML pipelines, ensure robust and reproducible deployments, and collaborate on technical solution design in a production environment. 🗂️ Requirements: University degree in Computer Science, Data Science, Mathematics or related field, Experience building and operating production-grade machine learning pipelines, Strong Python engineering skills with clean code practices, Experience with Git-based version control, Experience working with CI/CD pipelines, Experience with ML platforms and cloud-based ML environments, Fluent English, Fluent Polish, Availability to work in hybrid mode with 1–2 office visits per week 📃 Skills: Python, Git, CI/CD, Databricks, AWS, Azure, GCP, MachineLearning, DeepLearning 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML/deep-learning models, you are responsible for the technical design, implementation, and operation of productive ML solutions. You work in a tandem setup with an internal colleague who handles stakeholder management and overall coordination, allowing you to focus fully on modeling, pipelines, and technical execution. Design, train and optimize classical machine learning and deep-learning models for business-relevant use cases Build and maintain end-to-end machine learning pipelines covering data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of machine learning solutions in production environments Implement structured and versioned ML workflows supporting reliable model development and operation Collaborate closely with internal machine learning engineers and data teams on technical topics and solution design Benefits Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more. Language Courses – you'll have access to a multi-language learning platform enabling you to practice your language skills and learn new ones! Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development. Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions. Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Solid experience building and operating production-grade machine learning pipelines Strong Python engineering skills , including clean code practices and software engineering best standards Hands-on experience with Git-based version control and working with CI/CD pipelines as a user Experience with productive ML platforms and cloud-based ML environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: The role focuses on designing, building, and operating production-grade machine learning solutions using classical ML and deep learning models. You will develop end-to-end ML pipelines, ensure robustness and reproducibility in production, and collaborate on technical solution design. The position emphasizes strong Python engineering and experience with cloud-based ML platforms. 🗂️ Requirements: Degree in ComputerScience, DataScience, Mathematics or related field, Experience building production-grade machine learning pipelines, Strong Python engineering skills, Experience with Git-based version control, Experience working with CI and CD pipelines, Experience with cloud-based ML platforms, Ability to design, train and optimize ML and deep learning models, Experience ensuring robustness and reproducibility in production environments 📃 Skills: Python, MachineLearning, DeepLearning, Pipelines, FeatureEngineering, Deployment, Monitoring, Git, CI, CD, Databricks, AWS, Azure, GCP, Cloud, VersionControl 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML/deep-learning models, you are responsible for the technical design, implementation, and operation of productive ML solutions. You work in a tandem setup with an internal colleague who handles stakeholder management and overall coordination, allowing you to focus fully on modeling, pipelines, and technical execution. Design, train and optimize classical machine learning and deep-learning models for business-relevant use cases Build and maintain end-to-end machine learning pipelines covering data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of machine learning solutions in production environments Implement structured and versioned ML workflows supporting reliable model development and operation Collaborate closely with internal machine learning engineers and data teams on technical topics and solution design Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Solid experience building and operating production-grade machine learning pipelines Strong Python engineering skills , including clean code practices and software engineering best standards Hands-on experience with Git-based version control and working with CI/CD pipelines as a user Experience with productive ML platforms and cloud-based ML environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 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: 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: Entry-level ML role focused on supporting generative AI development through high-quality multi-modal data annotation and evaluation. The position involves working with sensitive data, ensuring accuracy and consistency, and contributing to process improvements in daily AI operations. It is an on-site role in Warsaw, offering a strong entry point into the AI field. 🗂️ Requirements: 0–3 years experience in data, operations, linguistics, analytics, or related fields, English proficiency, Proficiency in French, Italian, or German, Familiarity with machine learning concepts, Ability to follow detailed instructions with high accuracy, Strong attention to detail, Ability to work with multi-modal data, Ability to handle ambiguity and make logical decisions 📃 Skills: MachineLearning, DataAnnotation, DataLabeling, Multimodal, English, French, Italian, German, Analytics 🏢 Description: Junior ML Engineer Warsaw, 5 days per week from the office. Great entry point into the AI field. As a Junior ML Engineer , you’ll support the development of next‑generation generative AI by delivering high‑quality annotations across different data sources. Responsibilities Work with sensitive data while maintaining strict confidentiality. Label and evaluate multi‑modal data using internal tools and clear guidelines. Ensure accuracy and consistency across all tasks. Make logical decisions in ambiguous situations. Quickly switch between task types while keeping high quality. Spot process issues and suggest improvements. Support daily operations and help clarify internal queries. Requirements 0–3 years of experience in data, operations, linguistics, analytics, or related fields. English is a must have, and one of the following EU languages: French, Italian, German. Familiarity with machine learning concepts (can be gained during studies or academic projects). Ability to follow detailed instructions with high accuracy. Strong attention to detail and ability to work across different data types. Comfortable working with ambiguity and making reasoned decisions. Good communication skills and willingness to learn.

🏢 Summary: Staff Machine Learning Engineer role focused on leading Generative AI initiatives for manufacturing applications, including multimodal document understanding, structured data extraction, and AI systems combining text, images, and 3D data. The position involves developing and deploying large-scale AI models, shaping technical strategy, and mentoring engineering teams in a cloud-based production environment. 🗂️ Requirements: Bachelor's degree in Computer Science, Machine Learning, AI, or related field, 5+ years of machine learning or data science experience, Expertise in generative models, LLMs, or computer vision, Experience with large-scale language and vision models, Hands-on experience with multimodal data, Proficiency in Python, Experience with PyTorch or TensorFlow, Knowledge of probability, statistics, and optimization, Experience deploying ML models with cloud microservice architecture, Strong software engineering skills, Experience with CI/CD and version control, U.S. Citizen or Green Card holder 📃 Skills: Python, PyTorch, TensorFlow, pandas, NumPy, Transformers, GPT, VLMs, AWS, Terraform, CI/CD, OOP 🏢 Description: Xometry is seeking a Staff Machine Learning Engineer to lead Generative AI efforts focused on real-world manufacturing challenges, including multimodal document understanding, structured data extraction from technical drawings, and reasoning across text, images, and 3D data. Quick Facts - Lead the technical direction for the Generative AI team - Shape the AI roadmap and identify high-value AI opportunities - Develop and deploy large language and generative models - Build multimodal AI systems using text, images, and 3D data - Create scalable data pipelines and training workflows - Deploy models into production using AWS and cloud platforms - Collaborate with engineering, product, and business teams - Mentor teammates on advanced ML methods and best practices - Stay current with generative AI and deep learning research Requirements - Bachelor's degree required; advanced degree in Computer Science, Machine Learning, AI, or related field is a plus - 5+ years of experience in machine learning or data science - Deep expertise in generative models, LLMs, or computer vision - Experience with large-scale language and vision models including Transformers, GPT, and VLMs - Hands-on experience with multimodal data including text, images, and 3D - Proficiency in Python and ML libraries including PyTorch, TensorFlow, pandas, and NumPy - Strong knowledge of probability, statistics, and optimization - Experience deploying ML and AI models using cloud microservice architecture, preferably AWS - Strong software engineering skills including object oriented programming, testing, version control, CI/CD, and IaC with Terraform preferred - Strong communication skills across technical and business stakeholders - U.S. Citizen or Green Card holder required for ITAR compliance Benefits - 401(k) match - Medical, dental, and vision insurance - Life and disability insurance - Generous paid time off - Vacation, sick leave, floating and fixed holidays - Maternity and bonding leave - Employee assistance program and wellbeing resources Xometry is an equal opportunity employer. For U.S.-based roles, the company participates in E-Verify and will use Form I-9 information to confirm work authorization after acceptance of a job offer.

🏢 Summary: Senior GenAI Engineer role focused on designing and implementing enterprise-grade AI solutions based on LLMs, Agentic AI, and Generative AI. The position involves building end-to-end AI architectures, developing AI/ML pipelines, and integrating intelligent systems with cloud and business platforms. The role also covers MLOps practices and advanced NLP-based solutions including RAG architectures. 🗂️ Requirements: Minimum 3 years experience in Data Science / Machine Learning / Artificial Intelligence, Commercial experience with Generative AI, LLMs or Agentic AI, Very good knowledge of Python, Experience with TensorFlow or PyTorch, Experience with Pandas and Scikit-Learn, Experience with at least one agent framework: LangChain, LangGraph, AutoGen or Semantic Kernel, Knowledge of NLP: tokenization, embeddings, semantic search, RAG architectures, Experience with Azure, AWS or GCP, Knowledge of SDLC 📃 Skills: Python, LLMs, GenerativeAI, AgenticAI, TensorFlow, PyTorch, Pandas, ScikitLearn, LangChain, LangGraph, AutoGen, SemanticKernel, NLP, Tokenization, Embeddings, SemanticSearch, RAG, Azure, AWS, GCP, MLOps, CICD, SDLC 🏢 Description: Poszukujemy doświadczonego Senior GenAI Engineera, który będzie odpowiedzialny za projektowanie i wdrażanie nowoczesnych rozwiązań opartych o LLMs, Agentic AI oraz architektury AI enterprise-grade. Zakres obowiązków Projektowanie i rozwój rozwiązań opartych o: Generative AI / Large Language Models (LLMs) / Agentic AI NLP / intelligent automation oraz AI copilots Tworzenie i wdrażanie architektur AI end-to-end Budowa rozwiązań z wykorzystaniem: LangChain / LangGraph / AutoGen / Semantic Kernel oraz innych frameworków agentowych Implementacja i optymalizacja pipeline’ów AI/ML Rozwój praktyk MLOps: CI/CD / monitoring modeli / deployment / observability Integracja modeli AI z rozwiązaniami biznesowymi i platformami cloud Współpraca z zespołami developerskimi, DevOps oraz biznesowymi Rozwijanie nowych podejść i innowacyjnych rozwiązań AI dla klientów enterprise Wymagania Min. 3 lata doświadczenia w obszarze: Data Science / Machine Learning / Artificial Intelligence Doświadczenie komercyjne w obszarze: Generative AI / LLMs / Agentic AI Bardzo dobra znajomość Python Znajomość frameworków: TensorFlow / PyTorch / Pandas / Scikit-Learn Doświadczenie z przynajmniej jednym frameworkiem: LangChain / LangGraph AutoGen / Semantic Kernel lub podobnym Znajomość NLP: tokenization / embeddings / semantic search / RAG architectures Doświadczenie z Azure, AWS lub GCP Znajomość SDLC Bardzo dobra znajomość języka angielskiego Nice to have Doświadczenie w sektorze automotive i/lub financial services Znajomość: Docker / Kubernetes / Git / Azure DevOps Doświadczenie w MLOps i monitoringu modeli AI Znajomość Trusted / Responsible AI Język niemiecki lub francuski