Machine Learning Engineer Jobs

NVIDIA is seeking a Verification Engineer to join our ASIC Verification team, focusing on the design and implementation of industry-leading GPUs. This role involves verifying the ASIC design, architecture, golden models, and micro-architecture at the GPU and full-chip level using advanced verification tools and methodologies. You will build reusable components like bus functional models, traffic generators, monitors, checkers, and scoreboards, adhering to coverage-driven verification principles. The position requires understanding the design, defining verification scope, developing verification infrastructure, and ensuring design correctness, in collaboration with architects, designers, and pre/post-silicon verification teams.

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NVIDIA is seeking a highly enthusiastic and motivated Verification Engineer to verify the design and implementation of the next generation of control subsystems for the world’s leading GPUs. This position offers the opportunity to have a real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. We have crafted a team of outstanding people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the platform for the future of computing. At NVIDIA, our employees are passionate about parallel and visual computing. We are united in our quest to transform the way graphics are used to solve some of the most complex problems in computer science. The GPU started out as an engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. NVIDIA is increasingly known as “the AI computing company.”

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As an Executive Director Machine Learning Engineer on the Recommendation Engine team, you will implement fine-tuning and reinforcement learning algorithms on large compute clusters. You will build and run real-time and batch model serving systems, manage hyper-parameter tuning at scale, and oversee model monitoring and production validation. This role is vital for model development, testing, and deployment in a well-managed, controlled environment, supporting high throughput, low latency applications that leverage state-of-the-art machine learning architectures deployed in AWS. These applications power personalized experiences across Chase Consumer & Community Banking channels.

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Scale AI

Scale is seeking a Staff Machine Learning Research Engineer to join the Applied Intelligence Systems (AIS) team, which is part of the Scale Generative AI Platform. This role focuses on advancing agentic AI applications for enterprise and government use cases. You will work across the full spectrum of technical challenges within AIS, contributing to areas such as model training and fine-tuning, designing evaluation systems, building improvement loops from production data, prototyping novel agent architectures, and developing internal tooling. This is a hands-on research and engineering position where you will write code, ship production systems, and set the AI/ML technical direction for the team, influencing methods, architectures, and standards for others.

$250k - $350k

Veeam is seeking motivated students for their Summer Internship Program, designed for individuals entering their final year of university who are eager to gain real-world experience in a fast-paced, collaborative environment. The program runs from June to August 2027 and includes comprehensive onboarding, weekly professional development sessions, networking events, and social activities to foster personal and professional growth. Interns will have the opportunity to work on impactful projects, contributing to Veeam's mission as the Data and AI Trust Company.

$40k - $50k

Wayve is building the leading AI platform for autonomous driving, pioneering an end-to-end AI approach that enables vehicles to learn directly from real-world experience. This role sits at the center of our datasets team, which owns the driving data our AI Driver learns from, covering ingestion, annotation, retrieval, and data quality. As our data grows towards exabyte scale, deciding what data to keep and where is a major lever on both model quality and cost. You will shape the data that model engineers train on across the company, defining our dataset content strategy and steering data selection based on current model engineering needs.

$390k - $460k

OpenAI

OpenAI is seeking a senior Machine Learning Data Scientist to lead its forecasting initiatives within the Strategic Finance team. This is a founding role for the Forecasting pillar, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. The models developed will be crucial for predicting key business metrics like daily/weekly active users, revenue, lifetime value, compute consumption, and profitability, directly influencing critical business decisions and company strategy. This role requires a blend of technical expertise, product intuition, and business acumen, involving close collaboration with product managers, researchers, engineers, and finance leaders to operationalize insights and build foundational forecasting capabilities.

$347k - $445k

Salesforce is seeking a Senior/Lead Performance Engineer to join the SalesforceDB team, which manages the transactional database powering the Salesforce Platform. This role involves driving the design, scalability, and performance of our distributed database technology. You will identify and resolve performance bottlenecks, lead benchmarking efforts, and build telemetry to monitor production fleet performance. This is a fast-paced, collaborative environment where your work directly impacts the performance and scalability of a system handling trillions of transactions monthly.

$149k - $260k

As an Applied ML/AI Manager - Behavior Validation, you will lead a team focused on building and operating behavior critics and human benchmarking capabilities for ML-driven autonomy systems. Your team will translate subjective human expectations about safe, comfortable, and intuitive driving into rigorous, scalable evaluation frameworks that directly inform model development and release decisions. You will partner closely with autonomy, simulation, safety, and product teams to define how behavior is judged against human drivers and integrate behavior critic signals into validation pipelines, continuous release, and long-term performance monitoring.

$219k - $335k

10a Labs is seeking an Engineering Fellow to apply technical skills to high-impact research problems. This role involves contributing across the project lifecycle, from data processing and visualization to model deployment and cloud infrastructure building. It's a hands-on position at the intersection of applied research and engineering, offering opportunities to explore novel methods and generate insights. Fellows will specialize in Software Engineering, Data Engineering, or Machine Learning, collaborating with engineers on client-facing products and internal tools, assisting with research experiment design, and brainstorming new approaches in AI security and trust & safety.

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Scale AI

Scale is seeking a Staff Machine Learning Engineer for its Public Sector team to lead the design and deployment of agentic AI systems in critical government environments. This role involves working at the intersection of agentic ML, systems engineering, and applied research to build foundational infrastructure for AI systems that reason, plan, and act reliably at a national scale. You will partner directly with U.S. defense and intelligence agencies, contributing to flagship programs that advance agentic AI for geospatial reasoning, planning, and decision support. As a Staff ML Engineer, you will set technical direction, own core architectures, and translate ambitious ideas into production systems trusted by government operators.

$274k - $343k

General Motors is seeking a researcher to develop and apply artificial intelligence and machine learning solutions for advanced manufacturing systems. This role will focus on applying AI/ML to real-world manufacturing challenges involving process improvement, quality, automation, production efficiency, and decision support. The researcher will work with multidisciplinary teams to develop new concepts, build prototypes, evaluate results, and help transition successful solutions into manufacturing applications.

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Scale AI

Scale is seeking a Senior Machine Learning Engineer to own the application of generative AI, agentic AI, computer vision, and reinforcement learning to mission-critical production problems. In this role, you will tackle challenges without established solutions, proposing and building architectures, and ensuring their performance in customer-dependent environments. The Public Sector Machine Learning team focuses on deploying advanced models to government systems, with a primary emphasis on agentic systems built on large language models. This includes developing agents for complex operational and planning tasks, integrating retrieval pipelines and production APIs, managing state for long-running tasks, performing geospatial reasoning, and creating evaluation tooling. The role also involves applying reinforcement learning and computer vision for defense applications, including evaluation, labeling efficiency, and multimodal model training. As a Senior MLE, you will have design authority over a capability area, making final decisions on team patterns and ensuring they function under real-world constraints like classified environments, limited compute, and strict correctness requirements.

$235k - $294k

Scale AI

Scale works with leading AI labs to accelerate progress in GenAI research, focusing on LLM post-training and evaluation. This role is on the evaluation pod, building benchmarks and diagnosing model failure modes in text and multimodal modalities. You will develop rigorous evaluations to reveal where and why frontier models fail, collaborating with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with foundation model labs to translate failure analysis into technical and strategic input for next-generation generative AI models.

$166k - $207k

Scale AI

The Machine Learning Engineer role at Scale focuses on applying advanced techniques in generative AI, computer vision, reinforcement learning, and agentic AI to enhance production environments for Scale's products and customer experience. Leveraging robust internal infrastructure and extensive datasets, ML engineers drive product improvements. The Public Sector team specifically deploys cutting-edge models for mission-critical government systems, working with large language models and computer vision. This includes developing agentic systems for complex challenges, building agent frameworks, and creating evaluation tools. Efforts also involve advancing reinforcement learning for LLMs and training advanced computer vision models for defense applications, including large-scale fine-tuning and developing generalizable foundation models.

$235k - $294k

Scale AI

The Human Frontier Collective (HFC) is a unique and exclusive expert network that brings together researchers, academics, and domain leaders from over 70 fields to shape the future of AI. With over 90% of members holding doctorates, the collective focuses on how frontier AI systems are built, evaluated, and governed. Members participate in high-impact AI/ML projects, collaborate on research publications, and gain access to a vibrant community network. This role offers opportunities to work on projects such as building AI safety guardrails, optimizing PyTorch models, and evaluating ML code, with the potential to co-author technical reports and research papers.

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10a Labs is seeking a Machine Learning Engineer to design, build, and evaluate advanced machine learning systems for AI safety and model evaluation applications. This role blends strong ML engineering with an experimental approach, tackling problems in reinforcement learning, model evaluations, language models, and multimodal systems. You will transform ambiguous technical questions into rigorous experiments and scalable systems, collaborating with a diverse team of engineers, analysts, and subject-matter experts to support leading AI organizations.

$130k - $200k

Cohere

Cohere is seeking a Senior Staff Data Engineer to lead the Data Foundation pillar of their Analytics and Data Insights team. This role is responsible for ensuring Cohere's data is trustworthy, governed, and accessible, managing the data warehouse, pipelines, access controls, and an agentic analytics layer. The position involves owning the full data lifecycle, from ingestion into BigQuery using Airflow and Cloud Run, to data modeling with dbt, and serving results through Looker, APIs, and analytics surfaces. The role also emphasizes infrastructure as code with Terraform and robust data governance practices, including VPC service controls and IAM patterns. The successful candidate will inherit a strong foundation and contribute to significant roadmap initiatives, including scaling the data framework, establishing an internal analytics agent with an evaluation harness, and centralizing institutional knowledge.

$275k - $450k

Scale AI

The Human Frontier Collective (HFC) Fellowship is a program that brings together top researchers and domain experts to collaborate on high-impact AI projects. As an HFC Fellow, you will apply your expertise to design, evaluate, and interpret advanced generative AI systems, gaining exposure to cutting-edge research and working with a diverse network of leading thinkers. This is a fully remote, independent contractor opportunity with a flexible schedule, offering a chance to contribute to influential ML projects, co-author research publications, and develop your AI expertise within a supportive community.

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Scale AI

The Human Frontier Collective (HFC) Fellowship is a six-month, fully remote, independent contractor opportunity designed to bring together top researchers and domain experts to collaborate on high-impact AI projects. Fellows will apply their expertise to design, evaluate, and interpret advanced generative AI systems, gaining exposure to cutting-edge research and working with an interdisciplinary network of leading thinkers. This role offers a flexible schedule, allowing fellows to set their own hours (10-40 hours per week), and provides opportunities for professional development through review projects, advisory roles, and research, contributing to academic visibility and professional recognition.

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We are seeking intelligent and curious individuals to join our Machine Learning team and advance our ML initiatives. You will develop deep learning models that drive our trading strategies, leveraging a substantial computing cluster with numerous high-end GPUs. The unique challenges of trading, including large models, non-stationary datasets, and competitive multi-agent environments, necessitate the exploration of novel techniques. Collaboration is key, with researchers, engineers, and traders working closely to train models, design systems, and execute trading strategies. Your role will involve analyzing market data, optimizing hyperparameters, troubleshooting distributed training, and studying model behavior in production. You will contribute to shaping the future of ML at Jane Street by training next-generation deep learning models for trading strategies and building foundational knowledge for new markets.

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Databricks

Databricks is seeking a Senior Software Engineer for its AI Runtime (AIR) team. AIR is a managed platform designed for large-scale GPU training and fine-tuning of AI models, providing customers with on-demand access to accelerators and a serverless experience that simplifies the complexities of provisioning, scheduling, and orchestrating multi-node jobs. As a Senior Software Engineer on AIR, you will be instrumental in building and scaling the systems that ensure large-scale training is fast, reliable, and effortless. You will lead the architecture and evolution of the managed GPU training stack, focusing on areas such as scheduling, distributed training performance, fault tolerance, and the developer experience for large-scale job operations. Beyond hands-on system development, you will contribute to the technical vision for AIR, mentor engineers, and collaborate with product, research, and platform teams to expand the impact of custom AI training at Databricks.

$160k - $225k

OpenAI

We are seeking a Researcher to lead our safety and alignment research, focusing on building systems that can distinguish valuable web content from spam, manipulation, and other adversarial or low-quality material. This role involves tackling the challenge of detecting coordinated manipulation that may not be apparent when evaluating individual pages in isolation. As AI advances the ease of producing convincing content at scale, you will be responsible for adapting detection systems to counter increasingly sophisticated adversaries. You will define the technical strategy, develop classifiers and evaluations, and influence how integrity signals shape Search's indexing and retrieval processes. Collaborating closely with Search and broader Safety and Integrity teams, you will leverage frontier models to enhance detection methods and implement them in production.

$380k - $850k

Wayve is building the AI platform for autonomous driving, enabling vehicles to learn directly from real-world experience and adapt at scale. This role is on the Vehicle Generalization Team, focused on making Wayve's core autonomy generalize across a wide range of vehicle platforms. You will work on pre- and post-training methods to improve AI model generalization, specifically addressing how models perform with changes in perception and embodiment across different vehicles. Your work will directly impact production programs with major OEMs.

$370k - $420k