Top Machine Learning Engineer Jobs in San Francisco Bay Area, CA

As an ML research engineer, you will develop systems using language models, curate datasets, set evaluation metrics, and scale semantic search processes.

You will build and maintain assessment ML systems, define evaluation frameworks, and collaborate with design teams to improve language proficiency assessments.

Design, build, and deploy machine learning solutions. Collaborate with teams to transform research into practical applications using large datasets.

You will design and develop machine learning systems for an AI-driven dating platform, focusing on personalized matching algorithms and natural language interactions.

Build systems for Mercor's hiring engine, including pipelines for indexing, sourcing, scoring, and conversion. Work with ML and backend technologies.

As a Machine Learning Engineer, you will design and train perception models for robotics, focusing on 3D perception systems. You will tackle complex physical challenges, optimize models for embedded hardware, and collaborate with cross-functional teams.

Develop and scale learning models for behavior cloning and reinforcement learning. Build data pipelines and evaluate model performance for integration into autonomous systems.

The role involves building and deploying AI-native data solutions, focusing on LLM and agent development, automation workflows, and data analysis, while leveraging cloud technologies.

The role involves leading machine learning initiatives to enhance automated testing for autonomous vehicles, improve model interpretability, and collaborate with cross-functional teams.

The role involves designing, training, and validating machine learning models for semantic mapping in autonomous vehicles, while collaborating with validation teams and ensuring coding best practices.

Lead design and delivery of large-scale ML and AI systems for Airbnb Community Support products. Develop and productionize LLM-based solutions (fine-tuning, RAG/search, evaluation automation, feedback learning, guardrails), collaborate cross-functionally with product and design, and shape early-stage AI initiatives through to production to improve customer support experiences.

Design and ship production-grade agentic LLM systems (chat/voice assistants) for customer service. Build, evaluate, and optimize LLMs and MLOps pipelines, collaborate with product and design, and advance RAG, fine-tuning, RLHF, multi-agent orchestration and evaluation tooling.

Join Ello as an AI/ML Engineer to create AI-driven educational products, enhance learning experiences, and analyze educational outcomes through machine learning.

As a Staff Machine Learning Engineer, you will design and implement AI-driven solutions, build ML infrastructure, and lead teams to deliver scalable systems for real-time recommendations.

Design, implement, and maintain large-scale real-time ML systems for an AI-powered DSP. Run experiments, build models (NLP, clustering, LLMs, recommendation), optimize performance, and collaborate with engineering teams to deliver scalable production ML products.

Develop and deploy manufacturing intelligence systems and machine learning models to enhance operational efficiency in production environments, collaborating across teams to achieve impactful solutions.

You'll lead the development of AI-driven systems for a dating platform, focusing on personalized matching algorithms and voice interactions. Responsibilities include designing ML pipelines, deploying models, and conducting experiments to improve user experience.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

Develop, train, evaluate, and deploy spatial generative AI models for home renovation and design. Define inference framing, prepare image-based datasets with labeling partners, iterate with user feedback, and deploy performant models into production architecture.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Machine Learning Engineer at Onyx, you will enhance agent and knowledge retrieval capabilities by implementing LLM-based graphs and advanced NLP algorithms, while collaborating with the team to improve user experience and product direction.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

Lead the design of advanced AI systems for healthcare, develop evaluation frameworks, and drive LLM development while shaping AI strategy in a collaborative environment.

The Machine Learning Engineer designs and optimizes algorithms for data analysis and workflow automation, collaborating with engineering teams and ensuring algorithm performance on edge devices and high-performance environments.

The Machine Learning Engineer role involves optimizing models for performance, utilizing CUDA, GPU scheduling, and collaborating on ML systems design.