Machine Learning Manager Jobs

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 This Recruiting team hires world-class talent across Machine Learning, Data Infrastructure, Autonomy, and Systems Engineering. In this role, you'll own full-cycle recruiting for these functions and partner directly with engineering leaders to build the teams driving Nuro's AI-first strategy. About the Work Own full-cycle technical recruiting: sourcing strategy, pipeline generation, interview coordination, and offer negotiation/closing. Partner with engineering leaders across Autonomy, Ml Research, Systems Engineering and Software Engineering to define role scopes, build interview plans, and set evaluation criteria. Track recruiting metrics (time-to-fill, pipeline conversion, source effectiveness) and use them to identify bottlenecks and improve processes. Run structured technical and behavioral evaluations in partnership with hiring panels to ensure consistent, defensible hiring decisions. Build and maintain sourcing pipel

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. Join NVIDIA's Nemotron Harness team. We are leaders in AI research, exploring machine learning, reinforcement learning, computer vision and natural language processing. As a Research Scientist, you will work on projects that seek to redefine general intelligence. This Zürich, Switzerland position offers an outstanding platform to participate in innovative research and impact the future of AI. What you will be doing: Conduct groundbreaking research to advance the science and technology of intelligent machines. Co-develop models with harnesses, increasing task horizon, improving memory and general intelligence capabilities in VLM/LLM systems. Work towards daring long-term research goals, while identifying and achieving immediate achievements. Influence the research community through high-quality publications and collaborative efforts. Open source high-quality code and ensure the reproducibility of your research. What we need to see: PhD or equivalent 6+ years of experience in Computer Science, relevant technical field, or similar, completed prior to joining NVIDIA. Research background in machine l

InMobi Advertising is a global technology leader helping marketers win the moments that matter. Our advertising platform reaches over 2 billion people across 150+ countries and turns real-time context into business outcomes, delivering results grounded in privacy-first principles. Trusted by 30,000+ brands and leading publishers, InMobi is where intelligence, creativity, and accountability converge. By combining lock screens, apps, TVs, and the open web with AI and machine learning, we deliver receptive attention, precise personalization, and measurable impact. Through Glance AI, we are shaping AI Commerce, reimagining the future of e-commerce with inspiration-led discovery and shopping. Designed to seamlessly integrate into everyday consumer technology, Glance AI transforms every screen into a gateway for instant, personal, and joyful discovery. Spanning diverse categories such as fashion, beauty, travel, accessories, home décor, pets, and beyond, Glance AI delivers deeply personalized shopping experiences. With rich first-party data and unparalleled consumer access, it harnesses InMobi’s global scale, insights, and targeting capabilities to create high impact, performance driven shopping journeys for brands worldwide. Recognized as a Great Place to Work, and by MIT Technology Review, Fast Company’s Top 10 Innovators, and more, InMobi is a workplace where bold ideas create global impact. Backed by investors including SoftBank, Kleiner Perkins, and Sherpalo Ventures, InMobi has offices across San Mateo, New York, London, Singapore, Tokyo, Seoul, Jakarta, Bengaluru and beyond. At InMobi Advertising , you’ll have the opportunity to shape how billions of users connect with content, commerce, and brands worldwide. To learn more, visit www.inmobi.com Who are we and What do we do? InMobi Group’s mission is to power intelligent, mobile-first experiences for enterprises and consumers. Its businesses across advertising, marketing, data and

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron’s Chemistry Lab plays a critical role in advancing semiconductor technology by developing analytical methods that support materials understanding, process development, defect characterization, and next-generation memory innovation. The team applies advanced chemical, optical, and surface characterization techniques to solve complex materials challenges across semiconductor manufacturing and research. We are seeking a highly motivated summer intern to contribute to advanced spectroscopy and nanoscale characterization projects focused on semiconductor thin films, surfaces, interfaces, and process-induced material changes. Working alongside scientists and engineers in Corporate Labs, the intern will develop and apply spectroscopy-based characterization methods, analyze complex materials datasets, and gain experience in experimental design, data analytics, and semiconductor materials research within an industrial laboratory environment. Responsibilities Conduct experiments using advanced spectroscopy and microscopy techniques to characterize semiconductor thin films, surfaces, interfaces, and related materials. Collect, process, analyze, and interpret spectroscopy data, including photoluminescence, fluorescence lifetime, Raman, and AFM-IR datasets, and develop visualization workflows to communicate results. Correlate spectroscopic signatures with material properties, process conditions, surface states, and defect behavior while colla

NVIDIA has transformed computer graphics, PC gaming, and accelerated computing for more than 25 years through exceptional technology and the people who build it. In semiconductor manufacturing, our role is to enable the ecosystem, not compete within it. We partner with fabs, equipment manufacturers, and software providers to make inspection, metrology, and manufacturing intelligence dramatically faster on the NVIDIA platform. Our team builds the software that makes this possible: models, adaptation and evaluation workflows, and deployable inference capabilities that partners integrate into their own tools. We work in environments where labeled data is limited and proprietary, distributions shift across tools and fabs, production budgets are tight, and software must operate inside air-gapped facilities. We’re seeking a Principal Systems Software Engineer for Semiconductor Inspection in Santa Clara. This is a hands-on architect role: you will define the approach, build it, evaluate it, and demonstrate the results. You will work across computer vision, time-series modeling, multimodal AI, anomaly detection, model adaptation, evaluation, and production inference. Success means technology that a fab or equipment vendor can integrate, operate, and trust—not only a successful internal demonstration. What you’ll be doing: Define and prototype AI system architectures spanning optical and e-beam inspection, wafer and mask inspection, metrology, defect review, equipment signals, and process data. Advance world foundation model capabilities for semiconductor manufacturing, including vision, time-series and multimodal representation learning, model adaptation, domain transfer, and data-scarce defect understanding. Develop workflows for defect detection, classification, localization, segmentation, nuisance filtering, ADC, AD

Our team is seeking to extend the internship of our current AI Research Intern for the TAO (Train, Adapt, Optimize) Multi-Modal Model Development project, recognizing their exceptional performance and strong alignment with the team’s research goals. Their innovative ideas and technical contributions have significantly enhanced our work. Given the rapidly evolving field of multi-modal AI, encompassing vision-language modeling, universal segmentation, and large-scale model training, extending this internship will provide further growth opportunities for the intern while strengthening our team’s capacity to develop scalable, high-impact AI solutions. Embark on an exciting journey with NVIDIA, a global leader in AI and accelerated computing. As an AI Research Intern focusing on multi-modal AI and vision-language model development within the TAO framework in Hanoi/HCM City, Vietnam, you will be at the forefront of advancing cutting-edge machine learning research. You’ll collaborate with a talented team of engineers and researchers dedicated to developing state-of-the-art deep learning models for tasks such as image segmentation, cross-modal understanding, and universal representation learning. This internship offers a unique opportunity to contribute to next-generation AI systems with real-world impact across industries—from autonomous vehicles to intelligent content understanding. What you'll be doing: Develop and fine-tune multi-modal AI models using NVIDIA’s TAO Toolkit and deep learning frameworks. Contribute to the design and implementation of vision-language models (VLMs) and universal segmentation systems. Conduct experiments and benchmarking to evaluate model accuracy, robustness, and scalability. Collaborate with cross-functional teams to integrate your research into production-le

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview At Arpalus, recently acquired by Instacart, we build AI-powered computer vision and AR technology that turns a phone camera into a precise sensing tool - real-time object detection, scanning, and spatial understanding shipped as a mobile product. Our tech runs on real devices, in real environments, under messy real-world conditions. We're a small, fast-moving team and we're looking for a Principal Computer Vision Engineer who already works that way too. You'll join our core AI team and help craft best-in-class perception systems thatpower our real-time retail analytics. You'll solve genuinely hard problems in computer vision, bridging the gap between cutting-edge research and highly optimized production pipelines. You'll work hands-on, architecting solutions that seamlessly blend classic computer vision techniques with moder

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. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Senior Site Reliability Engineer (SRE) - Security and Data Systems Our company is seeking a highly skilled Senior Site Reliability Engineer to join our team. We are a SaaS company specializing in securing large-scale systems. This role is a blend of software engineering and systems administration, where you'll be responsible for building and maintaining highly reliable, scalable, and secure infrastructure. You will be a key contributor, applying your expertise to automate manual processes and proactively solve complex problems before they become incidents, handling incidents, and includes on-call shifts. * This position requires the ability to access U.S. National Security information. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permanent Resident, Refugee, or Asylee. 22 CFR 120.15 ) upon hire. Responsibilities Platform & Reliability: Design, build, and maintain the core infrastructure that underpins our security SaaS offerings, ensuring high availability, performance, and scalability. This includes building and operating the tooling for our Snowflake data systems. Automation: Develop robust automation using code to eliminate toil and ensure consistency across our environments. You'll be a key driver in automating everything from infrastructure provisioning to application deployment and incident response. Security &amp

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Senior Site Reliability Engineer (SRE) - Security and Data Systems Our company is seeking a highly skilled Senior Site Reliability Engineer to join our team. We are a SaaS company specializing in securing large-scale systems. This role is a blend of software engineering and systems administration, where you'll be responsible for building and maintaining highly reliable, scalable, and secure infrastructure. You will be a key contributor, applying your expertise to automate manual processes and proactively solve complex problems before they become incidents, handling incidents, and includes on-call shifts. Responsibilities Platform & Reliability: Design, build, and maintain the core infrastructure that underpins our security SaaS offerings, ensuring high availability, performance, and scalability. This includes building and operating the tooling for our Snowflake data systems. Automation: Develop robust automation using code to eliminate toil and ensure consistency across our environments. You'll be a key driver in automating everything from infrastructure provisioning to application deployment and incident response. Security & Compliance: Work closely with our security teams to embed a security-first mindset into all our processes and infrastructure. You will be responsible for ensuring our systems and data platforms are compliant with industry standards. Incident Response: Participate in on-call rotations and be a primary responder for critical inci

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About Ray Data Team: Ray Data is Python-native data processing engine that is a one stop shop for all AI data processing needs. Ray Data provides performant, first-class integration with cutting edge AI frameworks using both multi-modal and structured data. The Ray Data team currently develops and maintains Ray Data . We are a team of engineers passionate about building a Data processing engine which is a one-stop shop for all of your ML/AI needs. We are looking for exceptional engineers to build, optimize, and scale Ray for modern and increasingly complex AI workloads. As part of this role, you will: Improve the performance of Ray Data and multi-modal batch inference use cases. Ensure efficient scaling across different stages of the Data pipeline in a heterogeneous environment. Building data loading solutions for production training workloads. Focus on stability and fault tolerance at high scale Working with customers and new age AI native companies in scaling their AI workloads. We'd love to hear from you if have: At least 3-4 years of relevant work experience Solid background in building scalable and fault-tolerant distributed systems Experience with data processing, database internals. Passionate about large

About BlockTech BlockTech is a fast-paced algorithmic trading firm at the frontier of global cryptocurrency derivatives and spot markets. We trade 24/7 across some of the most data-rich, fast-moving venues in finance, and we use that data to build smarter models, sharper signals, and more adaptive systems. Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL couldn’t be shorter. We’re growing fast, and we’re looking for a Quantitative Researcher with a strong machine learning toolkit to help us push that edge further. The role As a Quantitative Researcher on our trading floor, you’ll own ideas end-to-end from hypothesis and dataset construction through feature engineering, model training and backtesting, all the way to live deployment, monitoring, and iterative improvement. You’ll sit shoulder-to-shoulder with Quantitative Traders and Quantitative Analysts, and your work will directly drive how we price and trade. What you’ll work on Collaborating closely with traders to translate research insights into systematic trading strategies Designing, developing and deploying models for price prediction, signal generation, execution, and anomaly detection across crypto derivatives and spot markets using state-of-the-art AI and ML techniques. Building robust trading, backtesting and research infrastructure alongside our engineers, so promising ideas can move into production quickly and safely Owning models in production: monitoring live performance, diagnosing decay, and iterating on what you ship What we’re looking for A strong academic background in a quantitative discipline (Mathematics, Physics, Statistics, Computer Science, Econometrics, ML/AI, or similar), typically a PhD or an MSc with strong research experience Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep, intuit

About BlockTech BlockTech is a fast-paced algorithmic trading firm at the frontier of global cryptocurrency derivatives and spot markets. We trade 24/7 across some of the most data-rich, fast-moving venues in finance, and we use that data to build smarter models, sharper signals, and more adaptive systems. Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL couldn’t be shorter. We’re growing fast, and we’re looking for a Quantitative Researcher with a strong machine learning toolkit to help us push that edge further. The role As a Quantitative Researcher on our trading floor, you’ll own ideas end-to-end from hypothesis and dataset construction through feature engineering, model training and backtesting, all the way to live deployment, monitoring, and iterative improvement. You’ll sit shoulder-to-shoulder with Quantitative Traders and Quantitative Analysts, and your work will directly drive how we price and trade. You will: Collaborate closely with traders to translate research insights into systematic trading strategies Design, develop and deploy models for price prediction, signal generation, execution, and anomaly detection across crypto derivatives and spot markets using state-of-the-art AI and ML techniques. Build robust trading, backtesting and research infrastructure alongside our engineers, so promising ideas can move into production quickly and safely Own models in production: monitoring live performance, diagnosing decay, and iterating on what you ship What we're looking for A strong academic background in a quantitative discipline (Mathematics, Physics, Statistics, Computer Science, Econometrics, ML/AI, or similar), typically a PhD or an MSc with strong research experience Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep, intuitive grasp of overfitting, g

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE: Are you the person on your team who builds the agent everyone else ends up using? We're looking for an AI Engineer to join our Training Product team and do that at Baseten. You'll build AI-driven product features for the customers training and post-training frontier models on our platform, and you'll raise the ceiling on how Baseten itself uses AI internally, turning manual workflows into agentic ones that make every other team faster. You'll work directly with our research engineers to scope and build products, taking ideas from a research loop that already works internally to something customers can run themselves. This is a hands-on role with real autonomy. You'll pick the problems worth solving, build the harnesses, execution flows, and guardrails that make AI systems reliable, and own the results. If you've been shipping agents and want that to be the job, let's talk. EXAMPLE INITIATIVES: Take a look at these blog posts written by members of our team: Baseten Training: an autoresearch substrate Introducing Baseten Loops Harnesses are everything. Here's how to optimize yours. Building with NVIDIA Nemotron 3 Ultra and LangChain Deep Agents Code on Baseten RESPONSIBILITIES: Build and ship agentic product experiences, including chat-style and assistant-like interfaces, from prototype to GA. Design the harnesses, execution flows, and guardrails that make AI systems reliable in production. Build internal autom

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. We believe Plaid has the power to be the next-gen Credit Bureau - supporting large scale adoption of cash flow into the credit underwriting process. The Credit Decisioning platform team is responsible for building best-in-class cashflow based insights products that enable lenders to make more holistic lending decisions and empower broader access to Credit products for prospective borrowers. We own the systems and tooling that form the platform to build and serve these insights at huge scale, partnering with our Data partners to release new products yearly. You will be defining the future architecture of Credit insights products and executing against an ambitious product roadmap. You will partner with our Product, Data Science, and Machine Learning team to iterate on and productionize new insights that enable our customers to make more holistic lending decisions. Responsibilities: Leading technical architecture and execution across credit insights products: everything from data fetching and online feature serving for API requests, to offline production pipelines and tooling for model training. Scaling and evolving the architecture through an expected ~100x increase in load from deterministic factors