Machine Learning Engineer Jobs

We are seeking a Lead Machine Learning Engineer with a focus on MLOps to join our Recommendation Engine team. In this role, you will be instrumental in building and maintaining sophisticated pipelines for distributed model training on large compute clusters, as well as for batch and real-time model serving. You will also manage hyperparameter tuning at scale, model monitoring, and production validation within a well-managed, controlled environment. Our product, Personalization and Insights, delivers high-throughput, low-latency applications powered by state-of-the-art machine learning architectures deployed on AWS. These applications enhance personalized experiences across Chase Consumer & Community Banking channels, integrating traditional banking services with offerings in Travel, Merchant Offer Shopping, and Dining.

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Applied Intuition

Applied Intuition is seeking a Systems Engineer with strong robotics and software skills to join their autonomous trucking system team. This role involves owning requirements, architecture, and verification for various system components, translating customer needs into detailed specifications, and ensuring their implementation and testing. You will collaborate closely with software, hardware, safety, and test engineers, as well as OEM partners, to bring an L4 autonomous product to production. The position also includes leveraging and developing AI-assisted tools to automate engineering workflows.

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Abnormal Security

Abnormal AI is seeking a Machine Learning Engineer - I to join the Misdirected Email Detection (MED) team, which plays a critical role in preventing accidental data loss by detecting and blocking misdirected outbound emails. This is a highly applied role for engineers who thrive on building, iterating, and experimenting, focusing on developing practical, end-to-end ML solutions rather than solely on model training. You will be responsible for generating and refining features, testing hypotheses, averaging signals, and translating research ideas into production-grade systems, collaborating cross-functionally to turn customer needs into measurable product improvements. The ideal candidate combines a tinkerer's mindset with technical rigor, balancing innovation with production excellence to drive experimentation, scale solutions, and deliver reliable detection capabilities that create meaningful customer impact in real-world environments.

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Sieve

Sieve is a multi-modal lab focused on curating high-quality training datasets across video, audio, images, text, and 3D, aiming to solve the bottleneck in the growth of AI applications. As a perception-focused Machine Learning Engineer, you will build systems that transform raw sensor footage into training data crucial for robotics and world-model teams. This role requires a strong background in computer vision, particularly in shipping perception systems for robots, devices, or autonomous vehicles, and applying these skills to massive datasets.

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The Machine Learning Center of Excellence (MLCOE) at JPMorgan Chase partners across the firm to shape, create, and deploy Machine Learning Solutions for challenging business problems. As a Quant AI Summer Associate within the MLCOE, you will join a team of technologists, ML researchers, and engineers exploring cutting-edge research and applying the latest Machine Learning techniques to J.P. Morgan’s unique data assets. You will collaborate directly with traders, portfolio managers, quants, data scientists, and salespeople to drive the data-led transformation of our businesses. Our Summer Associate Internship Program offers professional growth and development through project work, mentorship, and engaging speaker series, with potential for full-time employment offers upon successful completion.

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OpenSpace is redefining how complex projects are built using an AI-powered Visual Intelligence Platform that leverages computer vision and spatial AI to provide construction teams with a real-time view of on-site activities. This role focuses on owning core algorithms for mapping, localization, image analysis, and 3D reconstruction using real-world construction site data. The position integrates advanced computer vision with modern machine learning methodologies, utilizing classical CV, deep learning (including transformers and multi-modal models), and probabilistic modeling to deliver meaningful customer insights.

CA$168k - CA$220k

SambaNova

SambaNova is seeking a Principal Engineer to own kernel-level drivers and low-level software for high-speed IO, memory, and networking subsystems within the DataScale® platform and RDU architecture. This role is central to delivering reliable, high-performance AI systems at scale. This is a hands-on Linux kernel and device driver role; it is not an application or platform software role. You will lead software bring-up of new silicon, deliver production drivers across the IO, memory, and network data paths, and debug complex issues spanning kernel, firmware, and hardware. This role suits an engineer with deep kernel and driver expertise and strong hardware fluency, who can operate in ambiguity and execute with high ownership.

$180k - $255k

The Production Mapping organization at General Motors is responsible for developing mapping solutions to support Autonomous Vehicle (AV) and Advanced Driver-Assistance Systems (ADAS) features, including Super Cruise. In this role, you will contribute to solving complex mapping challenges using machine learning, advanced algorithms, large-scale data processing, and cloud computing. You will be involved in the entire development lifecycle, from exploring vehicle data and developing models to building scalable data workflows, deploying solutions, and evaluating their performance. Areas of focus include machine learning, geospatial analytics, distributed data processing, workflow automation, and cloud-based software development.

$148k - $148k

The AI Kernels & Compilers team at GM is at the forefront of developing advanced automated driving technologies, aiming for a future with Zero Crashes, Zero Emissions, and Zero Congestion. This role focuses on transforming cutting-edge AI research into production-grade software that runs efficiently and reliably on real vehicles. The team builds high-performance GPU kernels and custom libraries essential for on-vehicle ML inference in ADAS and autonomous driving systems, ensuring core AI workloads are faster, more reliable, and easier to deploy under real-world constraints.

$170k - $258k

Nebius is building a full-stack AI cloud platform to support developers and enterprises from data and model training through to production deployment. As a Senior Machine Learning Engineer on the Applied AI team, you will own model and endpoint optimization from model artifacts through production deployment. Your work will span model internals, quantization, model compression, speculative decoding, KV-cache optimization, inference engines, and serving architecture to improve latency, throughput, memory efficiency, GPU utilization, and cost per token while preserving model quality and reliability. You will collaborate with kernel and platform engineers to investigate serving problems, compare configurations, and resolve performance and quality regressions, validating improvements through reproducible benchmarks and safe production rollouts.

$195k - $262k

ElevenLabs

ElevenLabs is seeking an experienced Data Engineer to join their Data team. This role involves building and scaling data pipelines, establishing best practices, ensuring data quality, and enabling self-service data access for various teams. The ideal candidate will own and streamline data pipelines from ingestion to delivery, ensuring reliability, scalability, and efficiency. They will also implement dbt best practices, data standards, and quality controls, and build self-service tooling with clear documentation to empower cross-functional teams to meet their data needs independently. A key aspect of this role will be creating AI agents to answer data-related questions for others.

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Nebius is building an agent-native search platform designed for AI systems, providing programmatic, low-latency search APIs for retrieving, filtering, and reasoning over real-world information at scale. As a Senior ML Engineer focused on Search Optimization, you will be instrumental in enhancing the quality of our search product across the entire stack. This applied ML and information-retrieval role involves identifying and addressing areas where search quality is lost, developing innovative approaches, and implementing them to achieve measurable improvements in production. You will work with real-world queries, large-scale search systems, and evaluation signals to boost relevance, recall, freshness, and overall result quality.

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At PwC, our data and analytics engineering team leverages advanced technologies to design and develop robust data solutions for clients, transforming raw data into actionable insights to drive business growth. You will focus on designing and building data infrastructure and systems for efficient data processing and analysis, developing data pipelines, integration, and transformation solutions. This role is part of a purpose-led and values-driven work environment that drives innovation and allows you to make a tangible impact.

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Nebius is building a full-stack AI cloud platform for the global AI economy, supporting developers and enterprises from data and model training through to production deployment. We are seeking a Senior ML Engineer to join a fast-growing team focused on an agent-native search platform for AI systems. This role involves developing and deploying machine learning models for retrieval, ranking, and indexing at scale, enabling AI systems to access real-time information. It's a high-impact position on a production system operating at web search scale.

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Turing

This role focuses on ensuring the quality and sensitive data compliance of enterprise data as it flows through our systems. You will be responsible for building machine learning models that detect and replace sensitive information like PII, PHI, and company-identifiable data in text and image formats. This involves developing detection models, validation infrastructure, adversarial test sets, and audit processes to guarantee data integrity and de-identification performance. You will work closely with a senior ML lead, focusing on hands-on engineering with a strong QA mindset, ensuring data remains useful and secure for downstream applications.

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Glean is seeking a Software Engineer to help build a scalable software-based platform, including enterprise search solutions. This role involves working across distributed systems, data pipelines, APIs, and user interfaces to deliver secure, high-quality products. You will contribute to a Work AI ecosystem that powers intelligent search, an AI Assistant, and scalable AI agents, leveraging a broad range of enterprise data and flexible LLM choices. The position offers the opportunity to shape how the world works by building systems used daily across major platforms and embedding agentic capabilities into an open, extensible stack.

$215k - $279k

Anthropic

As a TPU Kernel Engineer, you will be responsible for identifying and addressing performance issues across various ML systems, including research, training, and inference. A significant part of this role involves designing and optimizing kernels specifically for the TPU. You will also provide crucial feedback to researchers regarding how model changes affect performance. The ideal candidate will have a proven history of solving large-scale systems problems and demonstrating expertise in low-level optimization.

$280k - $850k

Inworld is a research lab and inference provider focused on real-time AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, real-time workloads. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more, serving over 10 trillion LLM tokens per month. We are looking for strong individuals from varied backgrounds who learn fast, thrive in ambiguity, and can demonstrate their experience in building, breaking, and understanding complex systems.

$250k - $300k

As an Onboard Autonomy Intern, you will contribute to a focused research or engineering project within the onboard driving stack. You will work with experienced researchers and engineers to prototype, evaluate, and improve algorithms or software using vehicle data, simulation, or production-oriented environments. Potential focus areas include sensor fusion, structured perception, ML planning and trajectory generation, local planning and controls, and guardrails and integration.

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Capital One is seeking Machine Learning Engineers passionate about leveraging cutting-edge open-source frameworks, advanced algorithms, and emerging technologies to drive AI transformations and scale production models. In this role, you will be part of a collaborative team focused on solving complex business problems in a fast-paced, iterative environment. You will have the opportunity to design, build, and deliver ML models and components, inform ML infrastructure decisions, and automate tests and deployment.

$179k - $205k

Capital One is seeking passionate Machine Learning Engineers to join their Machine Learning Foundations (MLX) team. In this role, you will be at the forefront of driving AI transformations and scaling production models across the company. You will collaborate with product and data science teams to design, build, and deliver ML models that solve real-world business problems. This position involves leveraging cutting-edge open-source frameworks, advanced algorithms, and emerging technologies in a fast-paced, collaborative environment.

$179k - $205k

As an Onboard Autonomy Intern, you will contribute to a focused research or engineering project within the onboard driving stack. You will work with experienced researchers and engineers to prototype, evaluate, and improve algorithms or software using vehicle data, simulation, or production-oriented environments. Potential focus areas include sensor encoders and fusion, structured perception, ML planning and trajectory generation, local planning and controls, and guardrails and integration.

$142k - $142k

NVIDIA is seeking an enthusiastic and motivated Verification Engineer to verify the design and implementation of next-generation control subsystems for their leading GPUs. This role offers the chance to make a significant impact in a dynamic, technology-focused company, contributing to product lines spanning consumer graphics, self-driving cars, and artificial intelligence. You will be a key member of the ASIC Verification team, contributing to the verification of graphics and compute features within an IP, and will be responsible for IP-level verification of GPU ASICs. This includes working with specifications, developing test plans, tests, and verification infrastructure using UVM methodology, and ensuring functional and code coverage of all RTL.

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NVIDIA is seeking a Design Engineer to design and implement the next generation of control subsystems for GPUs. This role offers the opportunity to impact product lines ranging from consumer graphics to self-driving cars and artificial intelligence. You will be a key member of the ASIC Design team, contributing to the design and implementation of graphics and compute features within an IP, and responsible for the micro-architecture and RTL design of GPU ASICs. You will collaborate with architecture, verification, and physical design teams to deliver high-quality designs that meet performance, power, area, and timing goals.

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