Top Machine Learning Engineer Jobs in San Francisco, CA

Build and deploy scalable AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize model performance, latency, throughput, cost, and hardware utilization across production platforms. Own complex AI architecture, reliability objectives, security, and compliance reviews while contributing to technical roadmaps and mentoring engineering colleagues.

Designs and operates scalable machine learning and AI infrastructure on AWS, supporting training, inference, feature pipelines, LLM and agentic workloads, evaluation, observability, governance, and developer tooling. Builds distributed processing, streaming, infrastructure-as-code, and CI/CD systems while partnering with data science and ML engineering teams. Requires production experience with distributed systems, ML platforms, LLM application patterns, cloud infrastructure, containers, orchestration, and software engineering fundamentals.

Twelve-week Machine Learning Engineer internship developing, deploying, and operating production-scale ML models and pipelines. The intern will lead a research-to-production project, apply supervised, unsupervised, or reinforcement learning techniques, collaborate with engineering and product teams on blockchain and crypto use cases, and present findings to stakeholders.

Build datasets, evaluations, and scalable data infrastructure to improve frontier AI models for scientific and biological applications. Analyze model failure modes, design rigorous scientific tasks and evaluation criteria, run experiments, and collaborate with scientists and frontier AI labs. The role combines software engineering, biology, and frontier AI in an ambiguous, fast-changing environment.

Design, build, validate, and deploy machine learning models; perform EDA and statistical analysis; design and maintain scalable ETL/ELT data pipelines; work with large distributed datasets; run A/B tests; monitor production model performance; partner with product, engineering, and business teams to deliver data-driven solutions and ensure data quality.

The Model Behavior Engineer at Notion will ensure high-quality AI experiences through context engineering, data analysis, evaluative strategies, and collaboration with AI research labs. Responsibilities include designing tests, debugging, measuring quality, and developing systems to operationalize AI performance. This role blends product thinking with analytical skills to drive enhancements for AI tools.

Enable frontier AI models on Microsoft's Maia AI accelerators by integrating model architectures, optimizing performance, improving serving capabilities, and building validation and automation infrastructure. Diagnose issues across software, systems, and hardware layers; support hardware bring-up; and partner with model, runtime, infrastructure, and hardware teams to deliver reliable, scalable production AI workloads.

Build and operate scalable, low-latency machine learning backend systems for Samsara’s Safety AI products. Responsibilities include designing production ML APIs, developing data and evaluation pipelines, optimizing and serving model artifacts, processing petabyte-scale telematics data, monitoring model performance and drift, and integrating edge-to-cloud systems. The role partners with applied scientists, firmware engineers, platform teams, and product managers to deliver reliable safety features at fleet scale.

Join the IT AI Automation team to build and harden micro-apps and AI integrations on a governed GCP platform. Contribute to bug fixes, small features, code and design reviews, monitoring, and apply foundational software development and security practices. Gain hands-on experience with Python, SQL, CI/CD, and AI tools while supporting deployments, secrets management, testing, and documentation.

As a Staff Machine Learning Engineer, you will explore machine learning techniques, develop scalable systems, mentor junior engineers, and collaborate on strategic projects to enhance AI adoption at Coinbase.