Top Machine Learning Jobs in San Francisco Bay Area, CA

As a Machine Learning Engineer Intern, you'll tackle challenges in ML including training models, optimizing inference on GPU, and documenting findings.

As a ML Engineer at Wispr, you will design features for a voice interface, optimize ML inference, and scale personalization of speech models.

The Senior Engineer, Machine Learning develops audio and vision models for edge devices, collaborating with teams to implement and optimize ML solutions.

As an ML Engineer, develop and operationalize machine learning models, focusing on enhancing user experiences and novel architecture developments.

You will build frameworks for LLM-powered agents, design reinforcement learning approaches, lead development of scalable evaluation systems, and mentor other engineers while writing robust code for enterprise-grade assistants.

Lead team efforts in developing machine learning evaluation metrics and algorithms, enhance generative models, and ensure project alignment across multiple teams.

As a founding ML engineer, you'll build the core intelligence layer of our platform, focusing on model evaluation, SLM training pipelines, and real-time model routing, with opportunities for publishable research.

The Principal Analytics & ML Engineer will architect scalable analytics and ML solutions, build data models and pipelines, and mentor teams on best practices. Responsibilities include developing analytical models, collaborating across teams, and driving impactful analytics projects.

Design and develop scalable AI capabilities, integrating ML models and APIs. Collaborate with teams to ensure solutions meet security and performance standards in cloud environments.

The role involves designing scalable distributed systems using Scala, enhancing feature stores for performance, and collaborating with ML engineers to resolve challenges.

The Machine Learning Engineer Intern at Zoox will work on perception systems, developing algorithms for autonomous driving, collaborating with teams, and leveraging advanced machine learning models and datasets.

As an MLE Intern at Zoox, you'll create high fidelity synthetic data, develop AI models simulating road agent behavior, and enhance simulation tools for autonomous driving validation.

The ML/AI Engineer will define machine learning direction, develop automated pipelines, integrate models, and collaborate with product teams to solve user problems.

As a Senior Machine Learning Scientist, you will develop multimodal foundation models using large-scale single-cell datasets to advance drug discovery, applying deep learning methods and collaborating with biologists and engineers.

Develop and implement machine learning models for evaluating disputes and chargebacks, and create a model orchestration layer. Collaborate on data use for enhanced user experiences.

The Machine Learning Scientist will use insitro's TherML platform to develop oligonucleotide designs and collaborate across teams for drug discovery.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

The Senior Machine Learning Engineer will develop AI products, support feature implementation, and troubleshoot ML services to enhance customer experiences.

The role involves applying AI/ML techniques to develop model systems for healthcare, collaborating across teams, and conducting R&D.

The Senior ML Engineer will automate component placement on PCBs, working on R&D and production using ML and optimization techniques.

As an AI/ML Engineer, you will develop and optimize machine learning models, collaborate with teams, and enhance mobile app features using AI techniques.

Develop and optimize machine learning models for search and recommendation systems, collaborating across teams and using advanced ML technologies.

The Staff Machine Learning Engineer will define and build ML capabilities, design production systems, and lead ML strategy in a high-growth AI cybersecurity company.

The Machine Learning Engineer will own the ML lifecycle, develop production models, monitor performance, and collaborate with cross-functional teams to enhance business onboarding and fraud prevention applications.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.