Machine Learning Engineer Jobs in San Francisco

Databricks

The Applied AI team at Databricks is at the forefront of advancing GenAI-powered products, having launched Databricks Assistant, AI/BI Genie, and Agent Bricks. These products are used by hundreds of thousands of users daily, tackling challenging problems like code suggestion, text-to-sql generation, and knowledge QA. As GenAI products evolve, we are seeking engineers to drive the next phase of development, focusing on enhancing LLM quality, expanding GenAI capabilities, and strengthening platform architecture for AI interactions at scale.

$190k - $285k

Applied Intuition

Applied Intuition is building a robot learning platform to enable any robot to learn industrial tasks and continuously improve. The robotics team develops this platform and uses it to deliver robot autonomy on customer lines, training, evaluating, and deploying policies on real robots performing industrial tasks. This role involves hands-on work with hardware, seeing your contributions reach customers, and working on manipulation policies from task definition to reliable execution on a physical robot. You will train and fine-tune policies, diagnose failures, and ensure their dependability for customer use, with success measured on the robot itself.

$150k - $300k

We are seeking a Senior Machine Learning Engineer to join our Clinical Team. In this role, you will be responsible for owning the tissue-class segmentation and labeling models for our ultrasound CT clinical analysis layer, along with the pipelines that support their training and verification. You will retune models as image inputs are updated and clinical indications expand, and define training/evaluation pipelines, datasets, and metrics from the ground up. A key part of this role involves collaborating with data labeling contractors, expert clinicians, and internal teams on labeling specifications, quality control, and dataset versioning. You will also play a crucial part in productionizing models into a versioned, HIPAA-bound analysis service, ensuring reproducible inference, per-prediction confidence, drift monitoring, and safe fallbacks.

$237k - $250k

NVIDIA is seeking a Senior Integration Engineer to join their autonomous driving team. This role focuses on accelerating the development, integration, evaluation, and deployment of end-to-end driving models. You will collaborate across model development, data, simulation, systems software, and vehicle engineering teams to transform evolving AI models into reliable autonomous driving functionality on NVIDIA's computing platforms. The position involves working with large-scale training infrastructure, simulation environments, and production vehicle platforms.

$152k - $288k

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SpaceXAI is building Super Intelligence to help humanity understand the universe, from supercomputers to Grok models and their suite of applications. The RL Environments team is seeking a Software Engineer to build systems that transform real-world data into high-quality environments and tasks for reinforcement learning. This role involves creating more realistic training environments and owning the platforms and quality layers for trustworthy data production at scale. You will collaborate closely with ML Platform and research teams to convert various data sources into training-ready environments, making high-quality RL data more accessible for model training efforts.

Salary not listed

NVIDIA is seeking a Principal Systems Software Engineer for Semiconductor Inspection to join their team in Santa Clara. This role involves defining, building, and evaluating AI systems for semiconductor manufacturing, focusing on inspection and metrology. The work spans computer vision, time-series modeling, multimodal AI, and anomaly detection, with a strong emphasis on adapting and deploying these technologies within partner environments. The goal is to create integrated, reliable, and fast AI solutions that can be operated by fabs and equipment vendors, even in air-gapped facilities with limited data and tight production budgets.

$272k - $431k

Cargo

Plaid is seeking a Senior Machine Learning Engineer to join their Fraud Data team. This role will focus on developing and deploying machine learning systems to enhance Plaid's fraud detection products. You will work across the full data science and machine learning lifecycle, from identifying new signals and experimenting with models to deploying and optimizing them in production. The goal is to continuously learn from real-world performance and customer feedback to protect customers from evolving fraud threats. You will lead projects from initial experiments through model deployment and ongoing improvement, identifying predictive patterns in Plaid's network data.

$229k - $315k

ASAPP

ASAPP is seeking an enterprising, talented, and curious Machine Learning Engineer to join their AI Engineering team. This role will focus on building and evaluating the core intelligence behind agentic AI systems, playing a key part in designing and owning evaluation frameworks that ensure quality, safety, and performance across complex agentic systems. The Lead Machine Learning Engineer will own and grow the evaluation platform that measures quality, safety, and performance across ASAPP's agentic AI systems, ensuring confidence in model and agent changes before they reach customers.

$170k - $190k

We are seeking a Staff Engineer to build and maintain the production systems that power our AI-enabled product capabilities. This role bridges ML systems, platform engineering, and site reliability engineering, focusing on moving machine-learning models and agentic workflows from prototypes to secure, observable, and continuously deployable production systems. You will partner with various teams to create a streamlined path from experimentation to production and ensure the ongoing performance and evolution of these systems.

Salary not listed

Mercor is a leading AI data company building the layer between human expertise and frontier models. Millions of domain experts are paid daily to train frontier AI models, and Mercor Enterprise brings this infrastructure to Fortune 500 companies to capture and translate their best people's expertise directly into agents. This role is a foundational hire on a new Data Platform team, responsible for the infrastructure that every data-driven team at Mercor runs on, including Snowflake, Fivetran, Airflow, and Hex. You will own how data is organized, access controls, operational costs, and reliability, setting standards for other engineers.

$160k - $500k

Anthropic

The Safeguards ML Inference Path team designs, builds, and operates the production infrastructure that powers Claude's ML-based safety systems. This role involves collaborating closely with safety researchers and inference engineers to bring new classifiers and novel classes of ML defenses to production, owning the research-to-production transfer of new safety technologies critical for every Claude model launch. The team builds for scale, serving thousands of ML classifiers for all requests on the token generation path and for every platform Claude runs on. Engineers will work at the intersection of machine learning, large-scale distributed systems, and AI safety, developing platforms and tools that enable safeguards to operate reliably at scale, with tooling and infrastructure used for every model launch.

$320k - $485k

Nunchux AI is building infrastructure to make multimodal generative AI faster, cheaper, and easier to build on. Founded by MIT PhDs and CMU Professor, the company leverages deep research expertise and production systems experience. The Role focuses on bringing new image and video models to the Modelverse platform, prioritizing speed to launch. You will own the initial integration, coordinate deployment with the cloud team, and work with product engineers on API and Modelverse integration. After launch, you will hand off optimization tasks and maintain the shared code for model integration and serving.

$170k - $240k

Nunchux AI is building infrastructure to make multimodal generative AI faster, cheaper, and easier to build upon. We are seeking a Machine Learning Engineer focused on post-training and evaluation to enhance the efficiency and quality of visual generative models. In this role, you will develop and validate post-training techniques, curate and manage data pipelines for training and evaluation, and build robust evaluation systems to measure model performance. You will also benchmark models against industry standards, ensure quality, and integrate cutting-edge research into production workflows.

$180k - $250k

Moveworks is seeking a Machine Learning Engineer to develop cutting-edge ML infrastructure for building and serving LLMs. This role is pivotal in constructing, optimizing, and scaling end-to-end machine learning systems, encompassing distributed training and inference pipelines for large language models, model evaluation and monitoring frameworks, and LLM latency optimization. The frameworks developed will serve as a robust foundation for hundreds of ML and NLP models in production, impacting millions of enterprise employees. You will address challenges in service scalability and core algorithm optimization, working closely with machine learning, data infrastructure, and core skill teams. Your contributions will significantly influence customer AI experiences and the long-term scalability of our core AI product.

Salary not listed

Latitude AI, a subsidiary of Ford Motor Company, is developing the future of autonomous driving technology with its in-house ADAS platform, set to debut in 2027. The Intelligent Systems team focuses on converting sensor data into understanding through computer vision and machine learning, managing both onboard vehicle sensors and offboard cloud infrastructure. This role is within the Scalable ML team, which is crucial for improving the efficiency of model training and enabling ML developers to work effectively with large datasets to achieve optimal performance and advance transportation safety.

$179k - $269k

Anthropic

Anthropic's Safeguards organization is responsible for developing the policies, evaluations, and enforcement systems that prevent AI models from causing catastrophic harm. We are seeking a manager to lead our biological safety research engineering team. This team focuses on creating the evaluations, datasets, and classifiers that govern how our models handle biological knowledge. You will guide a team of research scientists and engineers in designing and executing capability evaluations on frontier models, curating safety classifier training data, and training/iterating on these classifiers. Your role involves setting technical direction, making investment decisions, and owning team outcomes, while maintaining technical depth to review designs and analyze failure modes. The team's core challenge is balancing robust safeguards against sophisticated actors with enabling legitimate researchers in the life sciences.

$405k - $485k