Senior Machine Learning Engineer Jobs

The Intelligent Foundations and Experiences (IFX) team is central to bringing AI vision to life at Capital One. We empower teams across the company with Generative AI models and platforms, enabling powerful, safe, and explainable AI capabilities like agentic workflows and shared services such as guardrails, observability, and evals. We also leverage foundational models, both open-weight and proprietary, and deliver capabilities to optimize the software development lifecycle, enhancing developer productivity and accelerating the time-to-market for machine learning models. We are seeking a Senior Director, Machine Learning Engineering who is passionate about leveraging cutting-edge open-source frameworks, advanced algorithms, and emerging technologies to drive major AI transformations and scale production models across Capital One.

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The Intelligent Foundations and Experiences (IFX) team is central to bringing AI at Capital One to life, empowering teams with generative AI models and platforms. These capabilities include agentic workflows, guardrails, observability, and evals, leveraging both open-weight and proprietary frontier models. The team also focuses on optimizing the software development lifecycle to enhance developer productivity and improve the time-to-market for machine learning models. We are looking for a Director, Machine Learning Engineering passionate about using cutting-edge open-source frameworks, advanced algorithms, and emerging technologies to drive major AI transformations and scale production models across Capital One.

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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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NVIDIA is seeking a research engineer to join the Isaac team, focusing on physical AI for robotics. This role involves developing simulation tools for scientists and companies leveraging machine learning in robotics. You will bridge the gap between Isaac product engineering and NVIDIA Robotics research, transforming research concepts into product features and providing user feedback to the research loop. The team works at the intersection of simulation and machine learning, aiming to create the leading tool for evaluating robot foundation models in simulation, building on NVIDIA's expertise in photorealistic rendering and physics simulation.

$184k - $357k

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 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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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

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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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

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

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

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