Ml Platform Engineer Jobs

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Payment Intelligence is comprised of multiple product teams building AI-first solutions to some of our customers’ biggest challenges, including fraud/abuse ( Radar ), payment optimizations ( AuthBoost ), Disputes, Authentication, and merchant analytics. We’re a mix of machine engineering engineers and full-stack software engineers impacting ~every Stripe transaction, creating revenue opportunities for Stripe and our customers, and helping protect the broader ecosystem. We have the benefit and privilege of working on cutting edge technologies with incredible scale and reach while also working directly with our merchants every day to build the right products for their needs. What you'll do As a Staff Engineer on Payment Intelligence, you’ll work across our product portfolio to ensure we’re building in a consistent, efficient, and effective manner. Experience with large, distributed systems on the critical path will help candidates succeed, as will comfort working across the stack and interacting with ML teams and models. Responsibilities Define technical strategy for multiple experiences across the Payment Intelligence portfolio, with a focus on quality and performance Champion a quality-first engineering culture - establish standards, tooling, and processes that make it easy to ship high-quality code at scale Partner with some of Stripe’s largest merchants to co-build the future of payment-centric intelligence Partner cross-functionally

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Our Growth team is on a mission to acquire, convert, and grow millions of merchants globally across the full Stripe suite of financial products. We're a cross-functional team of engineers, scientists, marketers, designers, and product managers that deliver the insights, algorithms, internal systems and tools, and user-facing experiences that fuel our growth. We help businesses around the world find Stripe, get started, and grow. As part of the Growth Engineering team, you'll build the systems, products, internal tools, and customer-facing experiences that power intelligence behind our go-to-market and product-led growth. This includes building ML-powered recommendations and growth experimentation engines, multi-channel notification systems, and key growth-related customer experiences (e.g., onboarding flows, user dashboards, product recommendations). What you'll do As a full-stack engineer on the Growth team, you'll build and ship experiments and product improvements across stripe.com and the Dashboard to help businesses find and get started on Stripe. You'll work on critical parts of the funnel for self-serve users, ensuring their experience on Stripe is consistently high-quality. With other engineers and data scientists, you'll turn ML-powered recommendations, messaging, and experimentation into impact that moves company metrics. Responsibilities Build and maintain scalable systems and customer experiences that help businesses discover, on

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Responsible AI team is part of the Advanced Technologies Group (ATG), Pinterest’s advanced machine learning team. ATG’s goal is to keep Pinterest at the forefront of machine learning technology across multiple use cases including recommendations, ranking, content understanding, and more. It is an applied team that works horizontally across the company on state of the art AI and ML and works on directly bringing that technology to the product in collaboration with product engineering teams. The team also publishes its work in applied research conferences, but the main goal of the team is to have a direct impact on business metrics. At Pinterest our goal is to inspire pinners (our users) to live the life they love. The product is powered by state of the art ML algorithms which are used to understand both the billions of visually rich items on

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Pinterest Labs group is dedicated to the development and research of applied machine learning. Our initiatives span a diverse range of AI/ML fields, including fundamental computer vision, multimodal large language models, multimodal representation learning, generative modeling, heterogeneous graph neural networks, and recommender systems. By building foundation ML models that utilize our extensive knowledge graph and billions of Pins, we aim to significantly enhance the core Pinterest product. Our visual modeling team is currently seeking new members to focus on the advancement of vision-centric LLMs. We are building VLMs capable of perceiving intricate visual details and understanding user aesthetics to facilitate communication through visual assets using tools like multimodal search and text-to-image models. This role offers the opportunit

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role The Data team manages the complete lifecycle of data for researchers - from sourcing and large-scale processing to delivering datasets that power our models. Data sits at the heart of our Research efforts and enables all other teams. As part of the Data team, you’ll work with over a million hours of video and audio data. This role exists at the intersection of applied research, data engineering, and ML infrastructure rather than being a traditional research position . You’ll build the world’s best human-centric data lake by collaborating closely with our model training teams. By understanding their requirements, you’ll extract new features and annotations that elevate our datasets. You should be passionate about enhancing model performance through high-quality, accurate datasets. Our infrastructure and pipelines are in great shape, and this role provides room to not only enhance them but also influence the team’s longer-term strategy. What we're looking for: A strong background in data-centric, applied Machine Learning, with hands-on experience improving model performance through data quality, curation, labeling, and evaluation rather than model architecture alone Experience working on the data la

What you’ll do Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability. Own core runtime foundations: distributed control, state management, fault handling, and reliability. Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes. Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints). Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes. Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress. What we’re looking for Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products. Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering). Track record of shipping systems that are observable, debuggable, and resilient. Strong technical leadership: clarity, pragmatic trade-offs, and mentoring. Useful experience Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling. High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review. Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior. Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI. Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We’re looking for a Staff Software Engineer to help build the next generation of Pinterest’s big data storage platform. You’ll work on some of the most exciting big data open source technologies — especially Apache Iceberg — at exabyte scale to power the data infrastructure that helps Pinners discover and do what they love. As a Staff Software Engineer, you’ll serve as a technical leader and hands-on contributor, designing and building highly scalable storage systems for Pinterest’s data lake. You’ll partner closely with teams across data, ML/AI, analytics, and infrastructure to evolve our storage and metadata management capabilities, enabling efficient, reliable, and governed access to data at massive scale. What you’ll do: Design, implement, and optimize Pinterest’s exabyte-scale data lake storage platform. Lead complex technical projects and

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else. What you’ll do: Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas Use data driven methods and leverage the unique properties

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . With more than 600 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else. Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads. What you’ll do: Build cutting edge technology using the latest advances in deep learning and machine learning to person

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . The CX Intelligence team is part of Coinbase’s Enterprise Applications and Architecture org and builds the customer-facing and internal CX experiences that connect the Help Center, chatbots (CBCB), and agent workflows. The team owns the multi-agent platform that powers Coinbase chat, Help Center, and agent tooling, partnering closely with Conversation Design, CX, and engineering teams to deliver secure, compliant, and scalable AI-powered support. Our work helps customers get answers faster while enabling agents to resolve cases more effectively. We are hiring an IC4 Machine Learning Engineer to help evolve our conversational ecosystem by building a seamless hybrid vendor-internal chatbot experience. You will contribute to the design and implementation of a unified orchestration layer that coordinates interactions between vendor AI, internal multi-agent systems, and human participants. This role is ideal for someone who enjoys solving complex ML systems problems, building reliable handoff logic across LLM frameworks, and shipping AI-enabled products that are measurable and scalable. What you'll do: Build and improve the orchestration layer that manages state transitions, context sharing, and intent routing across vendor and internal LLM frameworks in a distributed conversational environment. Develop production-grade Python services that bridge advanced AI and ML capab

Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games. Discord seeks a seasoned Data Engineer, focusing on our advertising product data. In this role, you will drive technical vision and strategy for ads data engineering in support of our ML initiatives while building and maintaining sophisticated data pipelines, datasets, and analytical tools. You will lead cross-functional initiatives to transform our advertising products through data-driven insights and mentor fellow engineers to deliver exceptional results. This role works heavily with Data Science, Machine Learning, and product. If leading technical innovation, architecting scalable solutions, and empowering teams through data excites you, we encourage you to make a move! What You'll Be Doing Design and own core ads data models : fact/dim tables, canonical datasets, and aggregation layers that power delivery, measurement, targeting, attribution, and ML use cases. Build and maintain the ML data that enables ads ranking, delivery, and targeting - including feature development, label generation workflows, intra-day training, and ML input observability to catch data quality issues before they degrade model performance. Build conversion measurement pipelines and integrate third-party attribution data - including Conversion Attribution and Mobile Measurement Partner (MMP) integrations (Adjust, AppsFlyer, Singular) - ensuring attribution accuracy and data parity across measurement surfaces. Build batch and near real-time pipeline infrastructure across the ads ecosystem - pushing toward lower-latency data for ML and reporting use cases on our BigQuery + dbt + Dagster stack. Partnering with Data Platform on lau

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Payment Intelligence is comprised of multiple product teams building AI-first solutions to some of our customers’ biggest challenges, including fraud/abuse ( Radar ), payment optimizations ( AuthBoost ), Disputes, Authentication, and merchant analytics. We’re a mix of machine engineering engineers and full-stack software engineers impacting ~every Stripe transaction, creating revenue opportunities for Stripe and our customers, and helping protect the broader ecosystem. We have the benefit and privilege of working on cutting edge technologies with incredible scale and reach while also working directly with our merchants every day to build the right products for their needs. What you'll do As a Staff Engineer on Payment Intelligence, you’ll work across our product portfolio to ensure we’re building in a consistent, efficient, and effective manner. Experience with large, distributed systems on the critical path will help candidates succeed, as will comfort working across the stack and interacting with ML teams and models. Responsibilities Define technical strategy for multiple experiences across the Payment Intelligence portfolio, with a focus on quality and performance Champion a quality-first engineering culture - establish standards, tooling, and processes that make it easy to ship high-quality code at scale Partner with some of Stripe’s largest merchants to co-build the future of payment-centric intelligence Partner cross-functionally

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The Big Data Infrastructure operates the critical infrastructure that powers the batch data processing at Stripe. The team supports a variety of use cases, including Payment, Ledger, ML, Fraud Detection, Product Analytics, Regulatory Reporting, Financial Data Reconciliation, and externally facing products like Radar and Sigma. As an example of the scale, the team's systems serve hundreds of teams, thousands of workflows, 100,000+ task executions, O(billion) transformations, and moving terabytes of data processing over 1 GB/second every day. Our users inside Stripe include other engineering teams, Data Scientists, Sales and Operations, Finance, etc. Data Orchestration builds and operates the time-based and event-based orchestration infrastructure that powers and accelerates batch data pipelines. The team operates on a wide range of tech stacks including Airflow, Spark, SQL, Kafka, Flink, Hive MetaStore, Trino, Pinot, Python, Java, Scala, S3, and Iceberg. What you'll do As a Software Engineer on this team, you'll design and build infrastructure that powers batch data processing at Stripe. Responsibilities Design, build, and maintain next-generation and first-generation versions of key Data Platform products, with an emphasis on usability, reliability, security, and efficiency. Design ergonomic APIs and abstractions that build a great customer experience for internal Stripes, that will in turn enhance the experience of millions of Stripe users.

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! Prior to applying please note: W e are currently unable to provide visa sponsorship for this position (including H-1B, OPT, or other employment-based visas). Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. This role is hybrid requiring 2 days in office at our San Francisco hub every Tuesday & Wednesday (located at 130 Sutter St). About the Role Machine Learning is a cornerstone at Taskrabbit, and we’re looking for a Staff Machine Learning Engineer to take technical ownership of our core ranking system. Every job request on the platform flows through it, making this one of the most consequential ML systems we run. This is a hands-on technical leadership role. You’ll operate as the primary architect and engineer for the ranking system — defining the system direction, driving the roadmap, solving the hardest problems, and creating leverage for the engi

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity! This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Key Responsibilities Co-design future hardware for programmability and performance with our hardware vendors Assist hardware vendors in developing optimal kernels and add support for it in our compiler Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory h