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We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. About the Team: Jobs change lives - ask any one of our millions of job seekers we serve and you’ll no doubt get a similar answer. At ZipRecruiter, our products help connect job seekers with employers, eager to add talent to their company. Our team works on applications at scale, serving millions of job seekers. We’re building an innovative marketplace for both jobs and job seekers alike. As part of this effort, we’re hiring an Engineering Manager to lead our Machine Learning Engineering team. Our business is complex and we’re looking for engineering managers who can own entire (or even multiple) product lines, drive business value while investing in their team’s/tech stack’s health, and coach engineers to build a strong culture of excellence, ownership, and personal and professional growth. About the Job: Own the mission, execution, morale, and code quality of your team Partner effectively with product managers to maintain and execute against the product roadmap Serve as a force multiplier for your team by removing roadblocks, identifying and implementing process improvements, and delegating effectively Actively build community and culture throughout the engineering organization Continually develop, coach, motivate, and improve your team, leading by example Champion and evolve innovation at ZipRecruiter and evangelize BIG ideas Minimum Q

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in AWS-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including AWS-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration. You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You should enjoy working with external technical partners, extracting the real goal from messy requests, and pushing back or reframing when the requested experiment is not the highest-leverage path. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time. In this role, you will Partner with strategic customers and in

About the Team The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-To-Market teams to inform high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we’re building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more. We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI’s full potential. About the Role We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability. This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You’ll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI. 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. In this role, you will: Build statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains. Own the end-to-end modeling lifecycle , including scoping, feature engineerin

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . We're looking for an experienced Senior Engineering Manager to lead our Media Ranking teams. In this role, you’ll lead a high-impact team of Machine Learning Engineers dedicated to improving relevance, personalization, and discovery of the core product. Reddit is investing big on making media (video and audio) as the core components of our experience around which conversations happen and users connect with the community. Your work will directly shape the personalized experiences of over 120M+ daily users. Responsibilities: Define Technical Vision & Strategy: Define the technical vision and long-term roadmap for Feed Relevance, aligning cutting-edge ML solutions with Reddit’s product and business objectives. Team Leadership & Development: Coach and support the development of your team, constantly seeking opportunities to grow their skills and impact. Cross-Functional Partnership: Work with cross-functional partners from across the company to identify key areas of opportunity, set expectations, and communicate your team’s work. Technical Execution & Delivery: Oversee the design, development, and optimization of sophisticated relevance, discovery, and content distribution systems. Platform & Infrastructure Collaboration: Collaborate with platform and infrastructure teams to chart a path to the next generation of AI-powered solutions for Reddit. Operational Excellence: Maintain high standards for system performance, reliability, and efficiency in alignment with customer needs and responsible AI princip

Perplexity is seeking an experienced Machine Learning Engineer to improve search quality across the middle and later stages of ranking. We are looking for a strong ranking generalist who can own ambiguous problems end to end and brings exceptional depth in either neural ranking or production ranking systems. Responsibilities Push search quality forward through models, data, evaluation, infrastructure, or any other leverage available. Own ranking-quality problems end to end: define the evaluation, identify the bottleneck, build the solution, and ship it safely. Train and evaluate retrieval, ranking, and classification models, including neural and LLM-based approaches where appropriate. Build and operate ranking infrastructure, including feature computation, low-latency inference, multi-stage cascades, deployment, and monitoring. Make sound trade-offs across quality, latency, reliability, cost, and engineering complexity. Collaborate across Data, AI, Infrastructure, and Product while retaining ownership of the final quality outcome. Qualifications Deep understanding of search or recommender systems and their evaluation. Proven ownership of a large-scale production ranking system or a substantial class of quality problems. Strong machine learning and software engineering skills across data, models, serving, and monitoring. Ability to drive ambiguous, cross-team problems without continuous task decomposition. Exceptional depth in either modern neural ranking methods or low-latency ranking systems and runtime.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . As a Senior Staff Machine Learning Engineer, Feed Relevance , you'll drive the development of GenAI-powered recommendations, leveraging Reddit’s unique community landscape, rich conversational data, and dynamic engagement patterns. Your deep modeling expertise will directly shape the core architectures behind feed ranking, enabling breakthrough personalization for tens of millions of users. Responsibilities: Deliver on technical initiatives that have significant company-wide impact Set technical direction for the broader Relevance and Feeds teams at Reddit, able to identify opportunities and influence strategy across multiple orgs Work with management on goal setting, planning, and de-risking critical projects Mentor and grow Senior and Staff engineers Create a strong healthy engineering culture Qualifications: 10+ years of industry experience building systems for relevance driven products Subject matter expert in relevance, recommendation, and ML systems; able to solve complex problems in these domains that few others can Deep understanding of how to build sustainable software systems at a large scale engineering organization Experience in influencing organizations on technical direction/best practices Experience working with cross-functional teams such as design, product, business & data teams to deliver great experiences. Strong focus on user experience, usability, scalability, reliability and quality. You are an undying advocate for the user, and you have a deep intuition for how people & machines inte

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. On the Underwriting ML team, you’ll build and improve machine learning systems that make real-time transaction decisions, assessing the repayment risk and expected value of every Affirm checkout. You’ll work closely with experienced ML engineers, platform partners, and cross-functional stakeholders to take models from idea to prototype to production, and to keep them healthy with strong measurement and monitoring as user behavior and macroeconomic conditions evolve. What you’ll do - You will develop and iterate on underwriting prediction models using a mix of approaches for tabular and sequential data - You will build and scale feature pipelines and training datasets from proprietary and third-party signals, partnering with data and platform teams when needed. - You will prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls. - You will help productionize models: integrate into batch and/or real-time decision systems, and improve reliability, latency, and operational robustness. - You will instrument and monitor model and data health, and help define retraining/backtesting workflows - You will collaborate across Engineering, Risk Analytics, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences. What we look for - You have a total of 2+ years of experience as a machine learning engineer or a PhD in a relevant field. - Strong Python skills and experience writing production-quality code. - Experience building and evalua

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. On the Underwriting ML team, you’ll build and improve machine learning systems that make real-time transaction decisions, assessing the repayment risk and expected value of every Affirm checkout. You’ll work closely with experienced ML engineers, platform partners, and cross-functional stakeholders to take models from idea to prototype to production, and to keep them healthy with strong measurement and monitoring as user behavior and macroeconomic conditions evolve. What you’ll do - You will develop and iterate on underwriting prediction models using a mix of approaches for tabular and sequential data - You will build and scale feature pipelines and training datasets from proprietary and third-party signals, partnering with data and platform teams when needed. - You will prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls. - You will help productionize models: integrate into batch and/or real-time decision systems, and improve reliability, latency, and operational robustness. - You will instrument and monitor model and data health, and help define retraining/backtesting workflows - You will collaborate across Engineering, Risk Analytics, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences. What we look for - You have a total of 2+ years of experience as a machine learning engineer or a PhD in a relevant field. - Strong Python skills and experience writing production-quality code. - Experience building and evaluating models for classification problems (preferably gradient-boosted decision trees like LightGBM/XGBoost/CatBoost, or similar). - Experience with a deep learning fra

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 highly technical Senior Engineering Manager with a deep understanding of modern recommendation systems to manage, lead and develop a team of ML researchers and engineers within the Applied Science team. In this role, you will lead the strategy of the Recommendation System innovation team. You will help the team build a balanced portfolio of work that addresses both immediate short-term business impact and long-term strategic breakthroughs in areas like Generative Recommendation System (GenRecSys), Large Sequential Models, and Reinforcement Learning (RL). Partnering closely with executive leadership, product management, and engineering partners, you will evolve our technical roadmap and directly drive Pinterest’s core mission forward. What you will do: Technical Vision and Execution: Own the tech

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is looking for an experienced Engineering Manager to lead our Feed Retrieval team. In this role, you’ll lead a high-impact team of Machine Learning Engineers building the systems that identify, retrieve, and shape the candidate inventory powering Reddit’s personalized feeds. Your team will work at the foundation of Feed Relevance: expanding the set of high-quality content Reddit can recommend, improving personalization and discovery for users across different levels of signal, and building scalable ML systems that directly shape the experiences of over 120M+ daily users. If applying ML / AI in production to improve Reddit Relevance excites you, then you’ve found the right place. Responsibilities: Define Technical Vision & Strategy: Define the technical vision and long-term roadmap for Feed Retrieval, aligning large-scale recommender-system investments with Reddit’s product, ecosystem, and business objectives. Roadmap & Prioritization: Translate broad Feed Relevance goals into a focused team roadmap, making clear prioritization tradeoffs across model quality, inventory expansion, experimentation velocity, infrastructure cost, and operational reliability. Team Leadership & Development: Coach and support the development of your team, constantly seeking opportunities to grow their skills and impact. Technical Execution & Delivery: Oversee the design, development, and optimization of retrieval systems that source relevant, diverse, fresh, and high-quality candidates for personalized feed experien

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is looking for an experienced Engineering Manager to lead our Feed Ecosystems team. In this role, you’ll lead a high-impact team of Machine Learning Engineers focused on building recommendation systems that support sustainable growth across users, posts, and communities. Your team will improve relevance for new, low-signal, and logged-out users; help new posts and communities find the right audiences; and develop ML systems that balance personalization, discovery, and ecosystem quality across Reddit’s 100,000+ active communities. If applying ML / AI in production to improve Reddit Relevance and strengthen Reddit’s community ecosystem excites you, then you’ve found the right place. Responsibilities: Define Technical Vision & Strategy: Define the technical vision and long-term roadmap for Feed Ecosystems, aligning recommender-system investments with Reddit’s goals around user growth, contribution, community health, and high-quality discovery. Team Leadership & Development: Coach and support the development of your team, constantly seeking opportunities to grow their skills and impact. Cross-Functional Partnership: Work closely with product, design, data science, safety, community, ads, and platform partners to identify opportunities, set expectations, and communicate your team’s work. Technical Execution & Delivery: Oversee the design, development, and optimization of ML systems that improve cold-start relevance, new post and community distribution, community discovery, and feed quality. Quality & E

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. With Roblox Ads business growing at a rapid rate, we are building large scale ads machine learning infrastructure to deliver effective performance ads to our users, and more business values to our advertisers. We’re looking for an EM to lead a team of exceptional ML infrastructure engineers, build scalable, reliable, and high-performance infrastructure that powers ML systems across our organization. You’ll operate at the scales of hundreds of billions of engagements, and redefine how we deliver performance ads to hundreds of millions of users. You Will: Lead strategic planning and roadmap execution of scalable production-ready ML systems including model training, data pipelines, feature engineering and model inference. Own the architecture, establish engineering best practices of scalability, reliability, and cost-effectiveness of ML infrastructure (e.g., training, serving, feature). Work closely with data scientists, ML engineers, platform teams, and product stakeholders to design, implement, and operate robust ML platforms that accelerate model development and deployment. Recruit, mentor, and grow a high-performing team of ML infrastructure engineers. You Have: 5+ years of experienc

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for an experienced Machine Learning Engineer to help us build the next generation of products which will go beyond just ID and enable our members to leverage the power of a networked digital identity. As a Machine Learning Engineer at CLEAR, you will participate in the design, implementation, testing, and deployment of applications to build and enhance our platform - one that interconnects dozens of attributes and qualifications while keeping member privacy and security at the core. A brief highlight of our tech stack: Python / Postgres / Snowflake / dbt AWS SageMaker and MLflow What you'll do: Own and drive the foundational work of a ML system at CLEAR Design, build and deploy ML models for various applications, such as document and image processing, fraud detection. Develop and implement robust data pipelines at a variety of scales, including collection, pre-processing, transformation, and feature engineering Partner with product and other stakeholders to uncover requirements, to innovate, and to solve complex problems Have a strong sense of ownership, responsible for architectural decision-making and striving for continuous improvement in technology and processes at CLEAR What you're great at: 3+ years of experience building, operating and scaling ML models for consumer applications, particularly those with experience building end-to-end systems Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Expertise in best practices for feature enginee

A Career with Point72’s Technology Team As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. What you’ll do Develop and maintain scalable artificial intelligence/machine learning (AI/ML) architectures and systems. Collaborate with data scientists, engineers, product teams, and Compliance to integrate AI/ML solutions into existing and new products. Evaluate tools, technologies, and processes to ensure the highest quality and performance of AI/ML systems. Stay abreast of the latest advancements in AI/ML technologies and methodologies. Ensure compliance with industry standards and best practices in AI/ML. What’s required Bachelor's or master's degree in computer science, engineering, or a related field. 3-7 years of experience in AI/ML engineering, with a proven track record of successful project delivery. Strong expertise in machine learning frameworks and libraries, such as TensorFlow, PyTorch, and/or Scikit-learn. Proficiency in programming languages such as Python, Java, or C++. Excellent problem-solving skills with the ability to work independently and collaborativel