Machine Learning Engineer

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 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. 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

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. The Community Support Products (CSP) Machine Learning team is the core team responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. The richness of Airbnb's data, the complexity of its marketplace and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to investing in long term innovation to solve the complex problems we face, and to do that we need the very best experts in ML and AI to join us. The Difference You Will Make: We believe our current customer experiences in these domains are only scratching the surface of the innovations that are possible, and that science is at the heart of delivering a step-function change for our Guest and and Host on Airbnb. You will build and leverage cutting edge AI technologies to transform Airbnb’s customer service by delivering personalized, easy-to-use and proactive customer service experience. Many of the initiatives you’l

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. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

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 535 million users around the world and 400 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,500 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. The Content Shopping Mining ML team builds machine learning systems that understand shopping-related content across the web, turning unstructured merchant pages into high-quality structured product data like price, title, availability, and images. This helps improve product experiences on Pinterest, including content quality, distribution, recommendations, and search; for example, see the team’s KDD 2025 paper,&

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. We are hiring a Machine Learning Engineer to join our ETA team. Our team builds and maintains Lyft's system responsible for estimating/predicting ETAs for every ride request on our platform. ETAs play a critical role in matching decisions, pricing estimates and overall user experience. Low latency, high reliability and high accuracy are paramount for our success. If you are a critical thinker with experience in machine learning workflows and writing reliable code, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. Our technology stack runs on AWS, Kubernetes, Go, Spark, Python and Apache Airflow. In this role, you will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on building rideshare experiences that delight millions of riders and drivers. Responsibilities: Perform data analysis and build proof-of-concept to explore and compare ML and non-ML solutions Be able to make effective tradeoffs between model accuracy, its productization complexity and runtime performance Develop statistical, machine learning, or optimization models Write production quality code that can scale well to serve millions of requests per day Participate in code reviews, design reviews, production on-call support and incident triaging process. Write well-crafted, well-tested, readable, maintainable code Experience: B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience 3+ years of Machine Learning experience Nice-to-have: Experience with big data processing / distributed data pipelines and tools such as Apache Airflow and Spark Ability to work in distributed teams spread across time zones. (North America and

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role We are a software engineering team with expertise in enabling ML models in production. We deploy AI models to run in variety of environments: air-gapped government networks, forward-deployed defense environments, edge nodes, and enterprises with strict data sovereignty requirements. Our customers rely on us for frontier AI capabilities running on hardware they control, often with constrained GPU resources and limited direct access. Rising to that challenge and meeting those expectations is what Palantir's excels at. We treat models like any other software: continuously tested, continually delivered, packaged for reproducible deployment, and built for long-term maintainability. You will own services end-to-end, and work across the full stack, from inference engines, GPU scheduling to deployment pipelines, observability, and integration with Palantir's platform. The goal is to deliver new models and capabilities quickly and continuously. Join us if you want to solve problems at the intersection of infrastructure and machine learning that directly enable critical customers.