Machine Learning Jobs in Berkeley, CA

Responsible for improving Zoox's HPC infrastructure, optimizing cloud/storage systems for ML workloads, designing APIs, and investigating distributed paradigms.

Design and develop auto-labeling algorithms for autonomous driving, collaborating with ML engineers to enhance data quality and efficiency in model training.

The role involves developing cloud solutions and enhancing ML/AI pipelines, ensuring service availability, and automating deployments in a scalable environment.

The Machine Learning Engineer will work with senior engineers to design and iterate ML solutions, manage data-centric workflows, and curate data for training models with a focus on computer vision and ML solution design.

The role involves assisting customers with the setup and optimization of FLUX models, collaborating on solutions, and deep product integration.

The role involves leading experiments to evaluate AI model performance, developing tools for rapid testing, and collaborating across teams to align model improvements with customer needs.

The role involves optimizing and deploying local large language models (LLMs), customizing ML models for real-world applications, and ensuring effective deployments in resource-constrained environments. You will work on AI systems that push the boundaries of technology and drive customer impact.

The AI/Machine Learning Engineer will design and implement ML solutions for healthcare, focusing on patient-centric applications and collaborating with experts to improve outcomes.

As a Machine Learning Intern at Ema, you will work on building and deploying machine learning models, analyzing datasets, and collaborating with senior engineers in a fast-paced startup environment.

Design and build backend systems for credit insights products, collaborating with various teams, and mentoring junior engineers.

Develop and optimize infrastructures for large-scale AI model training. Collaborate on end-to-end ML pipelines, ensuring efficiency and robustness.

The Senior Machine Learning Engineer will design and develop ML models for 3D assets, integrating AI into creator tools while collaborating with engineering and creative teams.

Lead ML Performance Optimization for autonomous driving, collaborating across teams, implementing optimization techniques, and mentoring engineers for career growth.

Develop and maintain the ML training framework, build inference services, lead design and implementation of ML platform, and mentor junior engineers.

The Machine Learning Engineer will develop perception models for interpreting 3D geometry, build multimodal pipelines, and collaborate with teams for deploying AI agents in engineering fields.

The role involves developing and optimizing scalable AI/ML systems, collaborating across teams, and enhancing workflows to support drug discovery.

Interns will conduct research in AI and machine learning, developing algorithms and collaborating with teams to enhance Adobe's digital experience offerings.

This internship involves enhancing Adobe Firefly's AI and generative technologies through research, collaboration, and integration of machine learning models.

As a Software Engineer in the ML Products team, you'll maintain and enhance systems for Twitch discovery, partner with applied scientists on ML model improvements, and collaborate with product managers for new experiences.

Develop and deploy ML-based perception algorithms for robotics, optimize pipelines, and collaborate across disciplines for integration.

The role involves designing, deploying, and improving machine learning models for identity verification and fraud prevention at Stripe, collaborating across various teams.

As a Machine Learning Engineer at Stripe, you'll design and deploy ML models, collaborate with various teams, and innovate using ML techniques to enhance products.

The role involves designing, building, and optimizing large-scale ML systems for personalized recommendations, focusing on data ingestion, model training, and collaboration with cross-functional teams.

Design, build, and optimize ML systems for recommendations at scale. Collaborate with teams on data pipelines, model development, and experimentation.

As a Staff Machine Learning Engineer, you will develop models and agents for AI integration into products, focusing on performance monitoring and issue resolution.