Machine Learning Jobs in Oakland, CA

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.

The ML Infrastructure Engineer will design distributed systems for ML training, optimize inference, build automation pipelines, and monitor production performance.

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.

Design and develop core AI systems for intelligent data matching and recommendation engines. Work with advanced AI and cloud technologies to enable data-driven insights.

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.

The Senior Software Engineer will develop and optimize the Machine Learning platform, enhancing ML lifecycle tools and supporting high-performance ML practices.

The Machine Learning Engineer will enhance ML systems and platform engineering, focusing on model deployment and mentoring junior engineers to optimize video-language modeling.

This role focuses on advancing reasoning in large language models (LLMs), requiring expertise in data strategy and model evaluation. The candidate will collaborate on research and bring solutions to real-world applications.

The role involves implementing machine learning features at Nooks, with responsibilities including training production models and aligning technical strategies with performance and cost.

As an ML Scientist at Wispr, you'll develop advanced voice interfaces, focusing on ML personalization and enhancing speech models using fine-tuning and reinforcement learning techniques.

The ML Engineer will develop voice interfaces, handle ML inference architecture, and enhance speech models for user personalization. Responsibilities include prototyping features and optimizing systems for high-volume requests.

As a Research Engineer, you will research human-centered AI mechanisms, evaluate alignment, and enhance Human-AI interactions through data-driven systems.

Design and implement RL and IL systems for robotic food manipulation. Develop algorithms for adaptive multi-agent coordination and integrate prototypes into production for commercial deployment.

As a Machine Learning Engineer, you will deploy models to production, manage data pipelines, and collaborate with partners, focusing on MLOps best practices.