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Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? As a Senior Machine Learning Engineer specializing in synthetic data, you will play a pivotal role in developing the synthetic data pipeline that is crucial to Cohere’s advanced language models. Your responsibilities will encompass the end-to-end management of synthetic data, including maintaining and optimizing the synthetic data pipeline, data analysis and generation, as well as conducting data ablations and model evaluation to gauge data quality. You will work with diverse web data and code data and transform them using generative models to improve token efficiency and model quality. By combining research and engineering, you will bridge the gap between raw data and cutting-edge AI models, directly contributing to improvements in critical training metrics like throughput and accelerator utilization. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective. You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. You Will: Model and Pipeline Automation Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models. Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models. Governance & Compliance Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards. Performance Monitoring Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. Incorporate user feedback for iterative improvements and manage necessary model retraining cycles. Cross-Functional Collaboration Act as the "glue" between Data Scientists (who build models

About the Team The Consumer Engineering Team is responsible for helping consumers discover and order everything they love globally. Our work spans the entire consumer journey across homepage, search, store discovery, item exploration, checkout and post checkout. We aim to craft a hyper-personalized, delightful and frictionless experience for millions of our customers. About the Role As a Senior Staff Machine Learning Engineer on Core Cx, you will set the personalization (P13n) strategy for the entire consumer shopping journey and bring that strategy to life. You will use our robust data and machine learning infrastructure to implement new ML solutions to make the consumer search experience more relevant, seamless, and delightful across restaurant, grocery, retail and all business at DoorDash . You will modernize the recommendation system leveraging AI. You will demonstrate a strong command of production level machine learning, experience with solving end-user problems, and collaborate well with multi-disciplinary teams. You're excited about this opportunity because you will… Drive the engineering vision, strategy, and execution for an organization of 150+ Grow, build, and nurture impactful business-focused product engineering teams. Scale the team by developing leaders internally and attracting world-class talent Mentor and guide a fast-growing organization in setting the right architectural patterns, working with various vendors in the space, and making judicious investments in the right areas anticipating what the company needs a few years down the road. Partner with Business, Product, and other Engineering teams to transform DoorDash from local commerce to agentic commerce We're excited about you because you have… B.S. or M.S. in Computer Science or equivalent. 10+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production. Proficiency in using AI coding tools (e.g., Claude Code) in th

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Our robotics team is growing and we are looking for a Software Engineer to join our Sensor Data and Calibration team. We are searching for an engineer with robotics and machine learning expertise to develop synthetic sensor simulation models and algorithms. The ideal candidate has hands-on experience in the research, development, and implementation of machine learning methods (e.g., NeRF or Gaussian splatting) for generating synthetic sensor data (photorealistic images, realistic lidar and/or radar, etc.). About the Work Research, develop, and implement state-of-the-art synthetic sensor simulation methods Analyze and characterize the realism and utility of synthetic sensor data Answer critical questions about sensor data and autonomy performance Collaborate with stakeholders across autonomy, infrastructure, and systems teams on map needs and requirements Role is scoped as a Senior/Staff IC with the flexibility to grow into

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: Everyone at Airbnb thinks about trust, but our team obsesses over it daily. At the core of trust is safety, and thus we spend a significant amount of our time and energy keeping the community safe. The Trust team is responsible for developing the technology that helps protect our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards. We constantly work to fight against online fraud (such as monetary loss, compromised accounts, spam and scam in messages, fake inventory, etc.) as well as offline fraud (theft, property damage, personal safety, etc.). We also work on onboarding and screening of users, and think about complex topics like identity and reputation to ensure that every interaction with Airbnb helps build trust in us and our community. Trust Engineering is responsible for the technology vision and development of a complex stack that runs on every key interaction on the platform. Trust Engineering is at the forefront of AI and ML innovation, helping develop novel techniques and advancing the state-of-art in Machine Learning to continually build and maintain trust across our platform. The Difference You Will Make: As a senior technical individual contributor, you will partner closely with our leaders across the broader technical organization helping design, execute and deliver in a complex and collaborative roadmap of Trust engineering efforts that will require collaboration across many parts of the organization and many parts of Airbnb. Although you will be at one of our highest levels of seniority, all individu

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: AI and ML 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 Core ML team is responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting Generative AI technologies to enable an intelligent, scalable, and exceptional service experience. The team develops and enhances AI models, ML services, and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning, and guardrails for a wide range of applications at 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 long-term innovation to solve complex problems, and to do that we need experienced ML ​​The Difference You Will Make: In this Senior Staff role, you will set technical direction and lead execution for ML evaluation and the end-to-end data flywheel powering CSxAI products (e.g., assistive agents, issue resolution, and tooling). Your work will define how we measure quality, how we turn feedback into learning signals, and how we continuously improve models and products safely and efficiently. You will partner closely with product, engineering, design, operations to build evaluation systems that are trusted, scalable, and actionable - connecting offline metrics to online outcomes. A Typical Day: Define evaluation strategy and suc

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: The Growth Platform team’s vision is to drive long term sustainable growth for the Airbnb community. Our mission is to build a best-in-class agentic system, and capabilities to support the growth of all Airbnb products, current and future. We achieve this by delivering highly personalized and relevant content and product experiences to the Airbnb community, both on and off of the Airbnb platform. The north star is full autonomy — where AI identifies opportunities, creates campaigns, personalizes experiences, and optimizes outcomes with minimal human intervention. We are progressing along a deliberate maturity curve: AI assisted → agentic → autonomous, with human-in-the-loop controls at every stage to ensure brand safety, quality, and compliance. The Growth Platform deeply integrates with the Airbnb product, understanding the customer journey and enabling differentiated customer engagement experiences to drive product growth. The platform also powers digital marketing channels including landing pages, email, push, SMS, and digital advertising, as well as the machine learning/AI and data platforms that feed into the management and optimization of these channels. The Difference You Will Make: As a machine learning engineer or scientist, your expertise will be pivotal in developing AI-powered solutions to shape the future of the Airbnb agentic growth platform with cutting-edge AI techniques. You will drive and guide the rest of the engineers to brainstorm, design and develop AI products and features from inception to production. We're seeking a Senior Staff Engineer who thri

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 CS AI product team is 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, alignment and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. The Difference You Will Make: As a senior staff machine learning engineer, you will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on Airbnb’s ML Infrastructure. You will partner with product managers, software engineers, data scientists and operation teams to brainstorm, design and develop AI products such as AI Assistant, Autonomous agent, recommendation, travel planning, and many more products that make meaningful impacts in the world of travel. A Typical Day: Work with large scale structured and unstructured data; explore, experiment, build and continuously improve foundation models for Airbnb product, business and operational use cases. Create a multi-year tech roadmap that enables our team to stay on the leading edge of the rapidly evolving AI landscape and

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role We are looking for a Senior/Staff Machine Learning Engineer to be a technical leader on Nuro’s Behavior & Planning team. Our team owns how the Nuro Driver behaves on the road: prediction, decision making, and planning, and is responsible for turning Nuro’s large-scale driving data into safe, comfortable, and natural driving behavior. In this role you will bring strong, general machine learning expertise to some of the hardest problems in autonomy and drive them from research through to deployment on real vehicles. You’ll work at the frontier of applied ML spanning areas such as foundation and world models, LLM/VLM reasoning, reinforcement and imitation learning, generative and diffusion models, and transformer-based prediction and planning. You’ll apply this knowledge and experience to make our driving generalize as we scale across new geographies as we expand throughout the U.S. and globally, and across new vehi

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. We are looking for a Senior Software Engineer specializing in Machine Learning to join our Revenue ML team at Discord. This team partners with our revenue product groups, focusing on both consumer revenue and our emerging Ads initiative. This role will specifically contribute to our Ads ML efforts, helping to build and scale ML capabilities in areas such as ads measurement, targeting, and delivery ranking. As part of this team, you will play a critical role in developing foundational ML models that enhance ad relevance, optimize performance, and drive revenue. This is a unique opportunity to work on an early-stage Ads ML platform and have a direct impact on the business's success. Our tech stack includes Python, ML frameworks like PyTorch and TensorFlow, large-scale data infrastructure, and real-time ad-serving technologies. What You'll Be Doing: Design, develop, and deploy machine learning models for ads targeting and ranking. Develop sophisticated ML solutions such as identity graph to enhance ad targeting. Build and optimize ad ranking models to serve the most effective ads based on campaign objectives (e.g., app installs, link click). Improve ads targeting and ranking by leveraging both on-platform and off-platform signals. Collaborate cross-functionally with product, engineering, and business teams to define and execute on the Ads ML roadmap. Scale our ML infrastructure to support an increasing number of concurrent ad campaigns while ensuring low-latency decision-making. Drive research and implementation of state-of-the-art ML techniques in the field of online advertising. What You Should Have: 5+

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Role Overview & Key Responsibilities This is a high-leverage leadership role that spans architecture, execution, and org-building, and will shape the direction of our AI / ML initiatives at Ema. We are seeking an AI / ML technical leader who can take a vision and build it. As a Principal ML Engineer at Ema, you will be a senior technical leader responsible for shaping the machine learning roadmap, architecting large-scale ML systems, driving innovation, and ensuring our mixture of expert models (LLM + SLM + Custom Model) is accurate and performant at scale. You will collaborate across teams (research, product, infra, data, etc.), mentor senior engineers, and influence strategy and execution at company-wide levels. Responsibilities Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products. Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning. Define and own the multi-year ML roadmap for GenA