Senior Machine Learning Engineer Jobs

Speechmatics is seeking a Senior Machine Learning Engineer to join their Research & Development team, focusing on cutting-edge speech technology. The company is a global leader in Voice AI, aiming to understand every voice through innovation and inclusivity. The Modelling Team trains diverse models, including large self-supervised ones, to enhance speech recognition accuracy and ensure their deployment into production using the latest ML developments and robust engineering practices.

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We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. At JPMorganChase, we believe in investing in our people — offering you the tools, mentorship, and environment to grow, innovate, and make a real impact. You'll be part of a culture that values diversity, inclusion, and continuous learning, where your contributions directly shape the technology that serves millions of customers worldwide. As a Software Engineer III at JPMorganChase within Corporate Technology, you serve as a seasoned member of an agile team to design and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. In this role, you will collaborate across teams to solve complex technical challenges, contribute to engineering communities of practice, and help drive a culture of excellence and innovation.

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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 is within the Generative Simulation team, which advances autonomous driving research by incubating new ideas. As a Machine Learning Engineer, you will develop next-generation world models and planners, such as GAIA, to simulate complex driving environments for faster training, broader testing, and scalable deployment. A major focus is on efficiency and interactivity, requiring models to run thousands of roll-outs per second, support closed-loop agent interaction, and fit within practical compute budgets. You will work at the intersection of machine learning research, multi-modal modeling, and real-world deployment, tackling challenges like deploying autonomous vehicles without real-world data and assessing if synthetic environments can replace physical testing.

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We are seeking a Technical Lead Manager to lead our Synthetic Data team, a critical component of our autonomous driving research. This role will focus on leveraging generative world models, like GAIA-3, to create a production engine for training-grade synthetic data. The goal is to significantly reduce our reliance on expensive on-road data collection by enabling the generation of diverse driving scenarios, even for future vehicle platforms or geographies where data collection is limited. You will lead a team of machine learning engineers, guiding technical strategy, system design, and the development of capabilities that accelerate our journey to AV2.0.

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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. The Model Integration and Release team owns the engineering release process for Wayve’s driving models, validating that new architectures, features, or data changes meet quality, safety, and performance standards before they reach customers. This role involves working across ML engineering, AI Platform, evaluation, and CI/CD to protect the model baseline while continually improving how reliably and efficiently models are delivered.

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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 is within the AV Core Engineering Team, specifically the Core Model Safety team, which focuses on collision avoidance, model understanding, and robustness under failure. You will join a senior team working with large-scale training and fleet data, collaborating with research, simulation, evaluation, and applied engineering teams. The core of the work involves leading large-scale data enrichment and curation initiatives, developing workflows for mining hard and rare events, investigating model performance in real-world scenarios, and improving the efficiency and reliability of the machine learning operations stack.

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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 is within the ML performance team, which optimizes inference for edge accelerators and GPUs, ensuring large transformer-based models run efficiently on low-cost, low-power in-vehicle compute. You will work closely with model, platform, and deployment teams to transform research models into reliable production systems for Wayve's driving product. This is a hands-on position involving ML systems, compilers, runtimes, kernels, and embedded deployment, focusing on identifying bottlenecks, implementing performance improvements, and collaborating with model developers on performance trade-offs.

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Runpod

Runpod is seeking a Senior ML Systems Engineer focused on Inference to lead efforts in making LLM inference the fastest and most cost-efficient on their platform. This role involves owning LLM serving performance end-to-end, measuring, understanding, and improving it across various models, hardware, and workloads. The work directly impacts customer latency and cost, requiring a hands-on approach to identify and fix bottlenecks, and ensure reliable production deployment. The ideal candidate will be passionate about AI infrastructure and contribute to building the platform for the next generation of AI developers.

$150k - $220k

Elastic

Elastic is seeking a Senior Software Engineer to join the Elasticsearch - Storage Engine team. This globally distributed, fully remote team focuses on developing core storage and query technologies for observability workloads. The role involves designing, implementing, and optimizing Elasticsearch's core storage and query engine, with a focus on improving storage efficiency, advancing query processing and performance, and optimizing data layouts. The company emphasizes empowering individual engineers, code review, consensus-driven decisions, and incremental improvements in a collaborative, asynchronous environment.

$133k - $253k

As part of the AI Engineering team within the Digital Assurance & Technology team, you will play a pivotal role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Assurance practice, you will focus on developing and implementing advanced AI and machine learning solutions to drive innovation and enhance business processes. Your work will involve designing and optimizing algorithms, models, and systems to enable intelligent decision-making and automation. You will set direction and quality standards across work streams and teams for testing and evaluation of AI-enabled systems, technical evidence and control effectiveness, and reusable capabilities that support responsible, reliable AI deployment across multiple teams. As a Senior Manager, you will leverage your skills and professional network to deliver quality results. You will motivate and coach others, collaborating to solve complex problems. With increased autonomy, you will apply sound judgment, recognizing when to take action and when to escalate. Your ability to develop and sustain diverse and inclusive teams, along with your commitment to excellence, contributes to the success of our firm. In this role, you will lead large projects and innovate processes, focusing on achieving results and maintaining operational excellence. You will interact with clients at a strategic level, driving overall project success. Your influence and skills will be crucial in crafting clear, impactful messages and applying systems thinking to identify underlying problems and opportunities.

$119k - $300k

Elastic

Elastic is seeking a Principal Software Engineer to join the Elasticsearch - Storage Engine team. This globally distributed, fully remote team focuses on developing core storage and query technologies for observability workloads. The role involves improving storage efficiency, advancing query processing and performance, and optimizing data layouts. The ideal candidate will drive the technical vision, architecture, and design of Elasticsearch's core storage and query engine, with a proven track record in high-performance, scalable database or search engine technologies and the ability to lead technical initiatives across organizations.

$160k - $304k

DevRev is seeking a Senior Software Engineer - Data Platform to contribute to the evolution of their AI-ready platform, "Computer." This role involves owning significant parts of the data architecture that powers DevRev Computer's memory, ensuring accurate and efficient data for insights and actions. You will design and operate scalable data systems, collaborating with engineering, AI Agent, Data Science, and Product teams to transform complex data requirements into reliable data products. This position is ideal for an experienced engineer passionate about large-scale data, distributed systems, database architecture, and performance optimization, offering substantial technical ownership and the chance to influence the direction of their agentic data platform.

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Artefact is seeking a Senior AI & Agentic Engineer for future opportunities. This role is ideal for an experienced professional with a deep understanding of data engineering and a proven track record of leading data projects in a fast-paced environment. The position involves designing, building, and maintaining scalable data pipelines, integrating complex data systems, and implementing CI/CD practices. You will collaborate with stakeholders to translate business requirements into technical solutions, oversee data engineering teams, and enforce data governance and security best practices. The role also includes optimizing data retrieval and developing reports, while continuously evaluating new technologies to enhance data engineering capabilities.

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SambaNova

As a Senior Principal Machine Learning Engineer, you will be responsible for designing, developing, and optimizing machine learning models, with a focus on cutting-edge Large Language Models (LLMs), to run efficiently on SambaNova's specialized hardware architecture, including the RDU. This critical role bridges advanced LLM research and practical deployment, involving the development of model architectures, improving training and inference efficiency, and collaborating on hardware-software co-design with compiler, systems, and hardware teams. The engineer will also act as the ML expert, guiding the integration of LLM solutions into production systems and customer-facing products like SambaStack and SambaCloud, with work spanning the full lifecycle from training and inference to evaluation and data curation.

$220k - $300k

As a Staff Data Engineer at Capital One, you will be a leading technical expert contributing to the future of data platforms and banking in the cloud. You will collaborate with data engineers, data scientists, machine learning experts, and product managers to devise scalable and reusable data solutions for complex problems. Your role involves driving innovation, optimizing business outcomes, and delivering strong data and technology solutions. You will promote engineering excellence, mentor junior engineers, and actively recruit talent to build our community. You will operate as a trusted advisor, sharing knowledge through communications, code samples, and blog posts, specializing in a particular subject area while impacting the organization broadly.

$269k - $307k

NVIDIA is seeking a Senior System GPU Performance Engineer to join their Silicon Co-Design Group. This role focuses on maximizing the performance and power efficiency of production GPU systems by analyzing workload behavior, silicon capabilities, software policies, and platform constraints. You will be responsible for identifying bottlenecks and implementing improvements, owning the entire process from hypothesis to root-cause closure and product impact. This is a hands-on role that turns complex system data into faster, more efficient, and predictable products.

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Anthropic

The Account Abuse team is responsible for ensuring Anthropic's computing capacity is allocated fairly by minimizing resources for bad actors and preventing their return. As a software engineer on this team, you will build the machine learning systems that detect and stop abuse at scale. The ideal candidate can anticipate opponent strategies and responses to countermeasures. This role involves full-stack machine learning engineering across model training, productionization, and evaluation, with opportunities to leverage Claude to accelerate model development and maintenance. The focus is on classical ML applied to structured and behavioral data, emphasizing robust production systems, precise measurement, and safe rollout strategies, as false positives can lead to legitimate customer lockout.

$320k - $485k

Latent is seeking a Machine Learning Engineer, Research, to lead the design and development of innovative modeling approaches that push the boundaries of clinical intelligence. This role involves driving research from initial problem definition to validated outcomes, influencing how models learn from longitudinal patient data. We are looking for senior and staff-level engineers adept at managing critical research challenges from inception to completion, with a focus on problems that directly impact patient well-being.

$225k - $300k

We are seeking Machine Learning Engineers passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. You will deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with Product, Architecture, Engineering, and Data Science teams. You will drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems and lead large-scale ML initiatives with the customer in mind.

$315k - $359k

Latent is seeking a Machine Learning Engineer to join their team and build systems that run in real clinical workflows. This role involves owning the design, development, and operation of production-grade ML systems from ambiguous problem definition through to reliable production deployment. The ideal candidate will drive systems end-to-end, setting technical direction and taking ownership of critical systems that directly impact real patient outcomes. This is an opportunity to work on mission-critical problems at the intersection of AI and healthcare within a fast-growing, early-stage company backed by top-tier investors.

$225k - $300k

Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One.

$269k - $307k

NVIDIA is seeking an AI Networking Architect to join the Networking Research Group. This role focuses on bridging the gap between emerging AI workloads and the data center infrastructure that powers them, operating at the intersection of AI applications, distributed systems, networking hardware, and software architecture. You will contribute to a team driving AI workload optimization through deep application understanding, network analysis, and end-to-end systems thinking. Your contributions will directly influence NVIDIA products across the entire stack, from applications and software libraries to hardware architecture and physical design.

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Capital One is seeking passionate Machine Learning Engineers to join their team and drive AI transformations. This role involves leveraging cutting-edge open-source frameworks, advanced algorithms, and emerging technologies to solve complex business problems. You will have the opportunity to build and scale massive multi-tenant platforms for ML model training and serving, inform infrastructure decisions with a deep understanding of ML techniques, and collaborate within cross-functional Agile teams to create state-of-the-art big data and ML applications. The position emphasizes writing and testing application code, developing and validating ML models, and automating tests and deployment, all within a fast-paced, collaborative, and iterative delivery environment.

$230k - $262k

PostEra

PostEra is seeking a Machine Learning Researcher to spearhead the development of an agentic research vertical. This role involves leveraging agentic systems to automate the creation of mechanistic models for biochemical and physiological processes, and to analyze biological data for target validation. You will collaborate closely with chemists and biologists to guide drug discovery decisions using these models. A key focus will be on developing machine learning methods capable of rapid adaptation to new drug discovery challenges with limited labeled data, particularly in molecular and tabular in-context learning and building foundation models from proprietary multimodal data. You will be responsible for the entire research loop, from defining tasks and constructing datasets to training and scaling models, performing rigorous ablations, and translating successful methods into practical capabilities for PostEra's scientists. While prior drug discovery experience is not mandatory, a strong motivation to learn the domain and collaborate with interdisciplinary scientists is essential.

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