Machine Learning Engineer, Trust & Safety

🏢 Summary: Machine Learning Engineer II role focused on designing, building, and deploying production-grade machine learning models that improve core product experiences and drive measurable business impact. The position emphasizes modeling, experimentation, and close collaboration with cross-functional teams to bring scalable ML solutions into high-traffic user flows. This is an individual contributor role centered on algorithmic innovation and end-to-end ML lifecycle ownership. 🗂️ Requirements: BS or MS in Computer Science, Machine Learning, Statistics, Mathematics, or related field, 2+ years of industry experience in machine learning, software engineering, data science, or related field, Strong knowledge of data structures, algorithms, and software design, Experience building or operating ML or AI systems, Proficiency in Python, Proficiency in at least one of: Java, Kotlin, Go, Scala, Strong understanding of model training, evaluation, and experimentation, Ability to design and analyze offline evaluations and online experiments, Experience writing production-quality code 📃 Skills: Python, Java, Kotlin, Go, Scala, Spark, Flink, AWS, Kubernetes, TensorFlow, TorchServe, Triton, Ray, Airflow, CI/CD, MLOps 🏢 Description: Our Mission As humans, there are few things more exciting than meeting someone new. At Tinder, we’re inspired by the challenge of keeping the magic of human connection alive. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day, and a presence in 190+ countries, our reach is expansive—and rapidly growing. We work together to solve complex problems. Behind the simplicity of every match, we think deeply about human relationships, behavioral science, network economics, AI and ML, online and real-world safety, cultural nuances, loneliness, love, sex, and more. Our Values Take the Lead: We don't ghost our work or each other. Just as users don't leave their matches hanging, we don't let each other down. Move Fast: We have a bias for action and urgency. Something that could be done tomorrow would be better if done today. Better Together: We keep connection at the heart of dating and at the heart of how we work. Just as our users are better when they connect with others, so are we when we collaborate. Real Talk: We say the hard thing the human way. Just as we ask our users to behave with kindness and candor in our community, we expect Team Tinder to do the same. Safety First: We act with integrity, transparency, and consistency so people feel safe—whether they're swiping, matching, or working alongside us. Spark Fun: We have fun to unlock creativity, fuel innovation, and help us build better experiences for daters. The Team or Role: The Tinder ML team drives impact across nearly every core domain of the product — Recommendations, Trust & Safety, Profile, Chat, Growth, and Revenue optimization. Our mission is to apply machine learning to enhance user experiences, foster trust, and accelerate business growth across Tinder’s ecosystem. ML at Tinder is organized into three groups with distinct roles: Machine Learning Engineers who focus on modeling and algorithmic innovation (this role) Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training, serving, and feature management Machine Learning Software Engineers who bridge the gap between research and production by delivering machine learning models into real-world product experiences at scale About the Role We are looking for a Machine Learning Engineer II to help build and ship machine learning systems that improve product experience and drive measurable business impact. This role is ideal for an engineer with a strong foundation in machine learning and software engineering who is excited to work on real-world problems, partner cross-functionally, and grow quickly in a high-impact environment. This is an individual contributor role focused on modeling and algorithmic innovation. You will work closely with product, engineering, data, and platform partners to translate product opportunities into machine learning solutions, run experiments, and help bring models from development into production. The team’s work directly translates into measurable business outcomes, and many of its models are embedded in core Tinder user flows at scale. Where You'll Work: This is a hybrid role and requires in-office collaboration three times per week in Palo Alto, California. In this role, you will: Translate product and business problems into clear machine learning problems with measurable success criteria Build, train, evaluate, and improve production machine learning models Partner with software engineers and ML infrastructure engineers to deploy models and improve reliability, scalability, and performance in production Design and analyze offline evaluations and online experiments to understand model impact Contribute to feature engineering, data preparation, training pipelines, and model monitoring Write clean, maintainable, production-quality code and participate in design and code reviews Communicate technical findings, trade-offs, and recommendations clearly to both technical and non-technical partners You'll need: BS or MS in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field 2+ years of industry experience in machine learning, software engineering, data science, or a related field Strong foundation in computer science fundamentals, including data structures, algorithms, and software design Experience building ML or AI-related systems, or strong understanding of how modern machine learning systems are developed and operated Proficiency in Python and at least one additional programming language such as Java, Kotlin, Go, Scala, or a similar language Strong understanding of machine learning fundamentals, including model training, evaluation, and experimentation Strong communication skills and the ability to collaborate effectively across functions Self-motivated, proactive, and comfortable taking ownership of well-scoped problems Nice to have: Experience with recommendation systems or casual inference Familiarity with big data or stream processing frameworks such as Spark or Flink Familiarity with cloud platforms such as AWS and containerized environments such as Kubernetes Familiarity with ML model serving frameworks such as TensorFlow Serving, TorchServe, Triton Inference Server, or Ray Serve Experience with feature stores, ML data pipelines, and orchestration frameworks such as Airflow Understanding of MLOps practices including CI/CD for ML, model versioning, and automated evaluation Exposure to observability and monitoring for ML systems Exposure to LLM-related use cases or applied generative AI projects As a full-time employee, you’ll enjoy: Flexible Vacation, 10 Sick Days Time off to volunteer and charitable donations matched up to $15,000 annually Comprehensive health, vision, and dental coverage 100% 401(k) employer match up to 10%, Employee Stock Purchase Plan (ESPP) 100% paid parental leave (including for non-birthing parents) and family forming benefits Investment in your development: mentorship through our MentorMatch program, access to 6,000+ online courses through Udemy, and an annual $3,000 stipend for your professional development Investment in your wellness: access to mental health support via Modern Health, paid concierge medical membership, pet insurance, fitness membership subsidy, and commuter subsidy Free subscription to Tinder Gold Commitment to Inclusion At Tinder, we don’t just accept difference, we celebrate it. We strive to build a workplace that reflects the rich diversity of our members around the world, and we value unique perspectives and backgrounds. Even if you don’t meet all the listed qualifications, we invite you to apply and show us how your skills could transfer. Tinder is proud to be an equal opportunity workplace where we welcome people of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Learn more here: https://www.lifeattinder.com/dei

🏢 Summary: Hybrid Android Engineer role focused on building and integrating AI-powered tools and agentic workflows to improve developer productivity and accelerate delivery of mobile features. The position combines native Android development with applied AI to design, automate, and optimize engineering processes. You will drive adoption of AI-native practices and measure their impact on velocity and quality. 🗂️ Requirements: 2+ years professional experience in native Android development, Strong proficiency in Kotlin, Deep understanding of large Android codebases and developer workflows, Experience with Android build systems and Gradle, Experience with CI/CD pipelines, Daily hands-on use of AI-native development tools, Experience with agentic coding workflows for code generation and refactoring, Experience building developer tools and automation scripts, Ability to measure engineering velocity and quality metrics 📃 Skills: Android, Kotlin, Gradle, CI/CD, Python, Bash, Claude, Codex, Cursor, LLM, OpenAI, Anthropic 🏢 Description: Our Mission Launched in 2012, Tinder® revolutionized how people meet, growing from 1 match to one billion matches in just two years. This rapid growth demonstrates its ability to fulfill a fundamental human need: real connection. Today, the app has been downloaded over 630 million times, leading to over 97 billion matches, serving approximately 50 million users per month in 190 countries and 45+ languages - a scale unmatched by any other app in the category. In 2024, Tinder won four Effie Awards for its first-ever global brand campaign, “It Starts with a Swipe”™ Our Values One Team, One Dream We work hand-in-hand, building Tinder for our members. We succeed together when we work collaboratively across functions, teams, and time zones, and think outside the box to achieve our company vision and mission. Own It We take accountability and strive to make a positive impact in all aspects of our business, through ownership, innovation, and a commitment to excellence. Never Stop Learning We cultivate a culture where it’s safe to take risks. We seek out input, share honest feedback, celebrate our wins, and learn from our mistakes in order to continue improving. Spark Solutions We’re problem solvers, focusing on how to best move forward when faced with obstacles. We don’t dwell on the past or on the issues at hand, but instead look at how to stay agile and overcome hurdles to achieve our goals. Embrace Our Differences We are intentional about building a workplace that reflects the rich diversity of our members. By leveraging different perspectives and other ways of thinking, we build better experiences for our members and our team.The Team or Role: We focus on AI × Developer Productivity and Workflow & Agents, building the culture, systems, and tools that let teams design, prototype, build, and ship connection experiences at record speed. As an Android engineer with an Applied AI focus, you'll sit at the intersection of mobile engineering and AI-assisted development, helping the team ship faster while raising the bar on how we build software. Where You'll Work: This is a hybrid role and requires in-office collaboration three times per week in Palo Alto, San Francisco, or Los Angeles, CA. In this role, you will: Build and maintain AI-powered Android tools and 24/7 agents that boost velocity and quality. Evaluate, integrate, and customize AI-native development tools for Tinder’s Android codebase and workflows. Develop prompts, templates, and agentic workflows aligned with Tinder’s architecture and coding standards. Measure and report AI tooling impact across the Android guild using clear velocity and quality metrics. Partner with engineers across teams to identify pain points and build tooling that removes friction. Drive guild-wide adoption of AI-native practices through documentation, workshops, pairing, and onboarding. You'll need: Relentless curiosity about how things work today and a drive to make them better. 2+ years of professional experience building native Android applications. Solid Android development experience in Kotlin with a deep understanding of large codebases and developer workflows. Strong experience with Android build systems, Gradle, and CI/CD pipelines. Demonstrated daily use of AI-native development tools (e.g., Claude, Codex, Cursor or similar). Hands-on experience with agentic coding workflows for code generation, refactoring, tests, migrations, and code review at scale. Experience building developer tools and automation (Python, Bash, Gradle plugins, custom lint rules, or similar). Systems-thinking mindset, able to see workflows end-to-end and spot high-leverage automation opportunities. Strong communication skills to evangelize new tools and practices, write clear documentation, and build buy-in across the guild. Collaborative and open to feedback, with empathy for other engineers’ workflows and pain points. Nice to have: Experience with prompt engineering and fine-tuning AI tools for domain-specific codebases Experience building custom MCP servers, IDE plugins, or developer experience tooling Familiarity with LLM APIs (OpenAI, Anthropic, etc.) for building custom AI-powered developer tools Background in developer experience, developer productivity, or platform engineering Experience measuring and improving engineering velocity metrics Commitment to Inclusion At Tinder, we don’t just accept difference, we celebrate it. We strive to build a workplace that reflects the rich diversity of our members around the world, and we value unique perspectives and backgrounds. Even if you don’t meet all the listed qualifications, we invite you to apply and show us how your skills could transfer. Tinder is proud to be an equal opportunity workplace where we welcome people of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Learn more here: https://www.lifeattinder.com/dei If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please speak to your Talent Acquisition Partner directly. #Tinder

🏢 Summary: Hybrid BD Operations Analyst role supporting Tinder’s Events Program by managing deal flow, contract lifecycle, partner coordination, and event supply operations within the app. The position focuses on CRM management, data reporting, quality control, and cross-functional collaboration with BD, Legal, Finance, and Product teams. It requires a detail-oriented professional experienced in operations and partnership processes within a fast-paced environment. 🗂️ Requirements: 2–4 years of experience in operations, partnerships coordination, account management, or similar role, Experience managing contracts, payments, or vendor/partner processes, Proficiency in CRM systems (e.g., Salesforce, HubSpot), Experience working with spreadsheets and data reporting tools, Ability to manage contract lifecycle and approval workflows, Strong cross-functional collaboration with BD, Legal, Finance, and Product teams, Ability to maintain accurate records and ensure data quality, Experience supporting operational workflows and process improvements 📃 Skills: Salesforce, HubSpot, CRM, Spreadsheets, DocuSign, Coupa, Data, Reporting 🏢 Description: Our Mission As humans, there are few things more exciting than meeting someone new. At Tinder, we’re inspired by the challenge of keeping the magic of human connection alive. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day, and a presence in 190+ countries, our reach is expansive—and rapidly growing. We work together to solve complex problems. Behind the simplicity of every match, we think deeply about human relationships, behavioral science, network economics, AI and ML, online and real-world safety, cultural nuances, loneliness, love, sex, and more. Our Values Take the Lead: We don't ghost our work or each other. Move Fast: We have a bias for action and urgency. Better Together: We keep connection at the heart of dating and at the heart of how we work. Real Talk: We say the hard thing the human way. Safety First: We act with integrity, transparency, and consistency so people feel safe. Spark Fun: We have fun to unlock creativity, fuel innovation, and help us build better experiences for daters. Description Tinder's Events program is building a new way for members to connect in person — and the operational backbone that makes it run is just as critical as the partnerships that power it. The BD Operations Analyst, Events Program is an IC role responsible for keeping deal flow moving, contracts clean, and event supply healthy on the Tinder platform. You'll sit at the intersection of the BD team, event host partners, and the product team — ensuring that what gets sourced in the field actually shows up in the app, accurately and on time. This is a detail-oriented, systems-driven role focused on making complex workflows run smoothly. You will collaborate daily with BD Managers, Legal, Finance, and Product. Responsibilities Operationalize deal flow across the Events BD team — tracking pipeline stages, maintaining CRM hygiene, and ensuring clean handoffs from sourcing through activation Manage the contract lifecycle for event host partnerships, including routing agreements for approval, coordinating payment processing, and maintaining accurate records Build and maintain relationships with existing event host partners, acting as a key point of contact for renewals, recurring deal logistics, and day-to-day questions Partner with the product team to manage event supply within the app — coordinating on listings, status updates, scheduling changes, and content accuracy Own quality control processes: review active and incoming event listings for brand alignment, content accuracy, and compliance with Tinder's policies Maintain clean, reliable data across partnership systems; build and distribute regular reports on supply health, partner activity, and deal metrics Identify operational gaps and propose scalable solutions as the program expands to new markets Support the broader BD team with ad hoc research, partner communications, and administrative workflows as needed Requirements 2–4 years of experience in operations, partnerships coordination, account management, or a similar detail-oriented role Strong organizational skills with experience managing contracts, payments, or vendor/partner processes Analytical mindset — comfortable working in spreadsheets, CRMs (Salesforce, HubSpot, or similar), and data reporting tools Clear, professional communicator who can manage multiple internal and external stakeholders simultaneously Proactive, process-improvement mindset Ability to work cross-functionally with BD, Legal, Finance, and Product teams Nice to Have Experience in the events, entertainment, hospitality, or consumer marketplace industries Familiarity with contract management or payment processing tools (e.g., DocuSign, Coupa, or similar) Background working alongside product or engineering teams Experience supporting a multi-market or high-volume partner portfolio Benefits Flexible Vacation, 10 Sick Days Time off to volunteer and charitable donations matched up to $15,000 annually Comprehensive health, vision, and dental coverage 100% 401(k) employer match up to 10%, Employee Stock Purchase Plan (ESPP) 100% paid parental leave and family forming benefits Annual $3,000 professional development stipend and access to 6,000+ online courses via Udemy Mental health support, paid concierge medical membership, pet insurance, fitness membership subsidy, and commuter subsidy Free Tinder Gold subscription Commitment to Inclusion We strive to build a workplace that reflects the rich diversity of our members around the world and value unique perspectives and backgrounds. Even if you don’t meet all the listed qualifications, you are invited to apply and show how your skills could transfer. Tinder is proud to be an equal opportunity workplace welcoming people of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or otherwise participate in the hiring process, please speak to your Talent Acquisition Partner directly.

🏢 Summary: Machine Learning Engineer role focused on designing, building, and deploying production ML systems across Lyft Business, including pricing, fraud detection, marketplace optimization, and agentic AI applications. The position involves owning models end-to-end, developing scalable ML infrastructure, and translating business problems into impactful ML solutions. The role operates in high-scale environments influencing revenue, operations, and user experience. 🗂️ Requirements: Experience with GenAI and LLM ecosystems, Experience building and deploying production ML models, Experience with pricing, marketplace, or fraud ML problems, Experience with feature engineering and ML pipelines, Experience with cloud ML services, Ability to productionize research prototypes, Experience running experiments and evaluating ML performance, Ability to design scalable ML systems, Proficiency in writing production-quality code 📃 Skills: Python, MachineLearning, LLM, GenAI, RAG, LangChain, LangGraph, SageMaker, Bedrock, AWS, GraphNN, KnowledgeGraphs, NetworkAnalysis, APIs, Experimentation 🏢 Description: At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Machine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust. Lyft Business builds products that help organizations move the people who matter most—employees, customers, patients, and guests—easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions. This role is ideal for someone who is technically versatile, energized by variety, and wants to see their work directly shape a large-scale business. Responsibilities: Develop and deploy ML models across multiple problem domains — including dynamic pricing, marketplace optimization, fraud detection, and anomaly/behavior detection — in production environments serving millions of rides Build and iterate on agentic AI systems (e.g., LLM-powered analytical agents) that automate decision-making and reduce operational overhead Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform Partner with Data Scientists on the Algorithms and Decisions teams to take research prototypes from proof-of-concept to production at scale Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement Identify new opportunities where ML can create leverage across Lyft Business verticals (Healthcare, Lyft Pass, Business Travel) and pitch solutions Contribute to team engineering standards — code quality, observability, documentation, and testing practices Experience: Experience with GenAI / LLM ecosystems — prompt engineering, RAG, agent frameworks (e.g., LangChain, LangGraph), or fine-tuning Exposure to graph-based ML methods (graph neural networks, knowledge graphs, network analysis) Experience with pricing, marketplace, or fraud-related ML problems Familiarity with cloud ML services (AWS SageMaker, Bedrock) or internal ML platforms Track record of identifying and scoping ML projects independently, not just executing on pre-defined specs Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible Subsidized commuter benefits Monthly Lyft credits and complimentary Lyft Pink membership Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law. Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid The expected base pay range for this position in the San Francisco area is $176,000-$211,200, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.