Machine Learning Jobs in Berkeley, CA

The internship involves working on machine learning research, focusing on frontier models and advanced training methods, while collaborating with industry and academia.

As a Senior Machine Learning Engineer, you will drive AI vision, develop models, and collaborate cross-functionally to enhance user experiences.

The Staff Machine Learning Engineer will lead ML strategy, architect AI infrastructure, mentor engineers, and develop impactful AI systems.

Design and build language models for AI security products, managing data pipelines, experiments, and model evaluations to ensure reliability and safety.

As a Senior/Principal Machine Learning Engineer, you will build ML systems for voice moderation, mentor engineers, and shape technical direction.

Lead cross-team engineering efforts to enhance ML-driven search relevance, mentor engineers, and develop foundational and relevant signals for search.

Lead the team responsible for the ML serving and deployment infrastructure at Pinterest, focusing on performance and productivity improvements while coaching team members.

Drive AI/ML-powered personalized experiences on Pinterest by defining product vision, collaborating across teams, and launching new features to enhance user engagement.

The Machine Learning Engineer will manage the end-to-end ML lifecycle, collaborate with cross-functional teams, develop production models, and monitor their performance in high-stakes environments.

Eluvio seeks an AI-Machine Learning Intern to build ML models, collaborate on data science solutions, and enhance video/audio content intelligence.

Interns will collaborate with the machine learning and data science team to build models for video/audio content using large datasets and provide actionable insights.

As an ML Engineer, you will design and develop ML solutions, build infrastructure for testing, training, and deploying models, and contribute to enhancing coding agent capabilities at Sourcegraph.

As a Research Engineer, you will collaborate on advancing AI systems through reinforcement learning, while contributing to both research and engineering tasks.

Design, build, and improve ML systems and infrastructure, mentor junior engineers, and write maintainable code in a customer-focused environment.

Lead machine learning projects by defining the ML system development life cycle, mentoring teams, and integrating models for urban perception tasks.

The role involves researching, implementing, and optimizing ML approaches for 3D simulation, collaborating with teams, and building scalable cloud pipelines.

Machine Learning Systems Engineers will develop end-to-end 3D machine learning systems, optimize training pipelines, and improve model performance within a collaborative team.

The Senior Staff ML Engineer will lead the architecture and implementation of Zendesk's GenAI platform, ensuring systems are secure and scalable while mentoring teams and aligning engineering standards with business goals.

Collaborate on designing recommendation systems, develop ML models, build infrastructure for deployment, conduct A/B tests, and ensure system reliability.

Develop and optimize computer vision and machine learning algorithms for autonomous tractors, focusing on perception tasks and sensor fusion. Collaborate with team to enhance real-time systems and improve accuracy in dynamic environments.

The Machine Learning Engineer will develop ML systems and platform engineering for video-language models, managing deployment, mentoring juniors, and optimizing model performance.

The role involves managing LLM training operations, optimizing GPU training on clusters, and collaborating with researchers on scalable machine learning infrastructure.

The role involves experimenting with ML models, building applications for speech and language, and continuous testing with a focus on autonomy and teamwork.

Lead research and implementation of cutting-edge ML methods, focusing on large-scale foundation models, deep learning, and drug discovery applications, while collaborating with interdisciplinary teams.

As a Machine Learning Engineer, you'll build ML infrastructure, develop scalable data pipelines for farm images, and collaborate with farmers and agronomists to apply ML solutions.