Senior Machine Learning Engineer Jobs

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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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

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

Lila is revolutionizing biomedicine by integrating large-scale automated data generation with advanced AI. We are building a system where AI, automation, and experimental biology work together synergistically. This role focuses on connecting that work to human medicine by developing systems that evaluate the biological validity of clinical programs. You will build the infrastructure to assess mechanistic support, ground biological mechanisms in human data, and evaluate clinical trial designs against proposed mechanisms. The goal is to create scalable systems that can rigorously assess and forecast program outcomes, ensuring scientific integrity and enabling public dissemination of findings.

$268k - $384k

Cargo

Plaid is seeking a Staff Machine Learning Engineer to join the Data Foundation & AI team. This team builds the shared ML and AI infrastructure that powers intelligent capabilities across Plaid's product suite, transforming unique financial network data into scalable, general-purpose representations. The role involves working at the intersection of machine learning infrastructure, applied AI, and distributed systems to establish the core AI platform that enables innovation. The Staff ML Engineer will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches. This position requires establishing rigorous evaluation frameworks, building scalable pipelines, and partnering with teams across the organization to define product integrations with foundation models. As a senior technical leader, you will mentor engineers, elevate engineering standards, and represent Plaid's AI and machine learning capabilities externally.

$249k - $368k

We are seeking a mathematically rigorous engineer to own model numerics, focusing on how we measure, bound, and reason about the numerical behavior of models and how this analysis informs deployment decisions. The core challenge involves determining if numerical differences between model versions are safe, connecting low-level concepts like floating-point drift to high-level outcomes like vehicle trajectory error. You will build the tooling to quantify these connections and define the thresholds for ship/no-ship decisions. This role requires more than just running existing validation; it demands the ability to investigate and explain the root causes of numerical divergence.

$171k - $261k

Databricks

Databricks is seeking a Staff Software Engineer for its AI Runtime (AIR) team. AIR is a managed platform designed for large-scale GPU training and fine-tuning of state-of-the-art AI models, providing customers with on-demand access to accelerators and a serverless experience. As part of this role, you will be instrumental in building and scaling the systems that ensure fast, reliable, and effortless large-scale training. You will influence the architecture and development of the managed GPU training stack, focusing on areas like scheduling, distributed training performance, fault tolerance, and the overall developer experience for operating jobs at scale. This position also involves defining the long-term technical vision for AIR, mentoring senior engineers, and collaborating with product, research, and platform teams to expand the impact of custom training at Databricks.

$190k - $265k

Lila is revolutionizing medicine by integrating automated large-scale data generation with scientific superintelligence. We are building a system where AI, automation, and experimental biology work together to tackle complex medical challenges. The Life Science AI team focuses on developing machine learning systems for analyzing biological data, combining advanced ML with cutting-edge biology. This role is crucial for building domain models that understand perturbation biology, genetics, and high-dimensional experimental data, linking biological mechanisms, experimental interventions, and therapeutic opportunities. The work involves not just learning from data but also guiding data generation and ensuring model outputs are interpretable and actionable for scientists and downstream systems.

$268k - $358k

Lila Sciences is developing a platform where AI and automation collaborate to address complex challenges in medicine, specifically within Life Sciences AI. The AI for Protein Engineering team focuses on creating and implementing generative and predictive models to advance biomolecule design programs from initial concepts to validated leads. This role is for a senior individual contributor specializing in computational biologics design, working on active protein engineering projects and enhancing Lila's capabilities in designing, evaluating, and learning from biomolecular data. The position is at the nexus of machine learning, protein engineering, and therapeutic design, requiring deep ML expertise, a strong understanding of protein biology, and a proven ability to deliver computationally designed, validated biologics.

$268k - $358k

Lila Sciences is seeking a Principal Machine Learning Engineer to join their growing Applied AI organization. This role focuses on adapting and improving AI models for customer-specific scientific needs, bridging the gap between cutting-edge model capabilities and real-world applications. You will be instrumental in shaping how Lila's AI models are fine-tuned, evaluated, and integrated into reliable workflows for customers. This is a senior individual contributor position requiring deep, hands-on expertise in model post-training, evaluation, and production ML systems.

$252k - $336k

Lila Sciences is seeking a Staff Engineer to lead the technical direction of its core data infrastructure. This role involves designing and evolving systems for ingesting, storing, and serving data critical to scientific discovery and machine learning workflows. You will work closely with scientists and researchers to translate requirements into robust platform capabilities, establish architectural patterns and engineering standards, and mentor other engineers. The position is ideal for individuals passionate about data system design who want to make impactful technical decisions.

$192k - $288k

Lila Sciences is building a platform where AI and automation co-evolve to solve complex problems in medicine. Within Life Science AI, Machine Learning engineers build and operate systems that transform foundation models into production capabilities for automated scientific discovery. This Principal ML Engineer role focuses on designing, building, and scaling the ML infrastructure behind these models, with current work in structure prediction, co-folding, sequence design, and multimodal scientific reasoning. You will own critical systems end-to-end, from training pipelines and distributed compute to model deployment and integration into Lila's discovery engine, shaping the technical direction for ML model training, evaluation, and deployment at scale.

$268k - $384k

We are seeking a Staff or Principal Software Engineer to join our Scientific System of Record Team and help define and build the next-generation AI-driven scientific platform. In this role, you will serve as a technical leader for systems that connect scientific intent, laboratory execution, data capture, and AI-driven analysis. You will shape the architecture of user interfaces, services, high-performance APIs, databases, and reliability-critical systems that integrate advanced AI frameworks with complex scientific analytics and laboratory workflows. You’ll work closely with ML researchers, platform engineers, data engineers, product teams, and scientists to turn complex scientific processes into scalable, elegant software systems. This is an opportunity to set technical direction for a cutting-edge AI platform with real scientific impact.

$204k - $310k

Lila Sciences is seeking a Principal Software Engineer, Instrument Simulations to architect and lead the development of their next-generation laboratory automation platform. This role involves designing the simulation infrastructure and integration layer that connects AI-driven experimental design with physical robotic systems, enabling closed-loop scientific discovery at scale. The company is building Scientific Superintelligence™ to solve humankind's greatest challenges by combining advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously.

$204k - $272k

Lila Sciences is seeking a Software Engineer to join a team that builds software powering the company's ML workflows and research tooling. You will collaborate with Machine Learning Engineers and Researchers to develop, support, and maintain Lila's ML libraries and tools. This role involves designing and building high-performance, secure, and well-documented Machine Learning libraries, creating CI/CD pipelines and integration tests for ML workflows, and architecting repository designs to follow consistent standards. You will also support debugging, logging, and maintenance for Ray-based compute environments and develop data ingestion pipelines linking lab data to ML teams.

$144k - $240k

EnCharge AI is developing a next-generation AI platform featuring a novel in-memory-computing architecture designed to significantly improve energy efficiency and performance for AI inference workloads. We believe that as AI demands evolve, the underlying infrastructure must also advance. Our team, comprised of experienced AI researchers, silicon and systems engineers, and architects, is backed by leading investors and is positioned to be a key player in the future of AI innovation.

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The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling tools and pipelines that power autonomous vehicle machine learning models. We operate at the intersection of software engineering, data engineering, and AI/ML, defining strategies, tooling, and quality controls for reliable training data at scale. This role offers end-to-end ownership of meaningful platform components, growth toward technical leadership, and direct impact on systems enabling the next generation of autonomous vehicle capabilities.

$175k - $261k

Capital One is seeking passionate Machine Learning Engineers to join a team focused on decisioning technology that guides customers through their credit journey. This role involves standardizing and streamlining the building, deployment, and monitoring of complex machine learning models at scale, reducing friction for data science partners. You will leverage a modern technology stack, primarily Python and Kubernetes, to create high-impact infrastructure supporting millions of customers in real time throughout their lifecycle. You'll have the opportunity to drive major AI transformations and scale production models.

$230k - $262k

Expedia Group is seeking a Senior Software Development Engineer to join the ML Platform team. This role is instrumental in building and evolving Expedia Group's Machine Learning Platform, which supports the entire ML lifecycle from feature engineering and training to real-time inference, monitoring, and cost transparency. The platform aims to reduce the barrier to entry for teams to safely and efficiently ship models at scale. You will contribute to designing, building, and improving scalable ML platform capabilities, ensuring high-quality software delivery, and enhancing platform reliability and performance. This position involves partnering with engineers and stakeholders to define technical strategies and influence the platform's direction, while applying strong technical judgment to balance immediate needs with long-term scalability and developer experience. The role also includes safely integrating and operating AI/ML-enabled solutions.

$185k - $258k

The Smart Agents group is responsible for building ML models and systems to simulate road users in various situations, generating scenarios for testing and training AV driving policies. This involves developing ML/AI models that control other characters in a simulation environment to interact realistically with autonomous vehicles. The technology stack includes Generative AI models (GPT) and Reinforcement Learning (RL) policies. The team collaborates closely with Simulation, Behaviors, Perception, and Safety Engineers. Specific duties include ML/RL model development, training loop development, optimization, integration, creating ML infrastructure, metrics, and data pipelines for production deployment and rapid experimentation.

$145k - $284k

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 work on the forefront of scaling production models and building massive multi-tenant platforms for ML training and serving. The position requires a blend of hands-on technical contribution, innovation, and leadership, including mentoring peers and junior engineers, and recruiting top talent.

$230k - $262k

Cresta

Cresta is seeking a Staff Machine Learning Engineer to work on high-impact AI initiatives, focusing on next-generation agentic AI systems that augment contact center agents in real-time. This role involves leading and building these systems, requiring strong ML foundations, deep expertise in LLMs and prompting techniques, and a rapid prototyping mindset to translate research into scalable, production-grade systems. The engineer will also focus on improving the reliability, robustness, and performance of LLM-powered agents by designing evaluation frameworks, diagnosing failure modes, and defining measurable quality metrics. Additionally, the role includes architecting and scaling LLM and retrieval-augmented generation pipelines to process complex data and deliver real-time intelligence.

$230k - $300k