Machine Learning Jobs in San Jose, CA

Support training and benchmarking of LLMs, evaluate datasets, and assist the Pathway Research Team to advance AI capabilities.

Lead the development of ML perception systems for autonomous vehicles, guiding the engineering team and mentoring machine learning engineers.

This role focuses on optimizing neural model architectures and systems for high performance across multiple GPU/TPU platforms, collaborating with various teams to enhance model efficiency and performance under real-time constraints.

The Senior Machine Learning Engineer will build machine learning models and innovative web applications for Generative AI, collaborating with teams to drive design and implementation.

The Senior Machine Learning Engineer will build and implement Generative AI solutions, coordinating with designers and product managers to enhance products and establish a data-driven culture.

Design and optimize software systems for deploying large deep learning models in autonomous vehicles, focusing on performance and efficiency.

This role involves developing deep learning algorithms for autonomous driving, optimizing neural networks, and leveraging multimodal datasets for reinforcement learning and decision-making.

The Senior ML Performance Engineer will architect a Performance Testing Platform, optimize ML performance on GPUs, and validate model efficiency.

Develop applications for a vehicle OS utilizing LLMs and NLP, focusing on user interactions and software module deployment.

Develop and integrate AI/ML solutions for various autonomous platforms, optimizing models for edge devices, and collaborating with defense stakeholders.

Interns will design hardware algorithms, develop proof-of-concept implementations, study trade-offs, and collaborate with ML model owners.

Lead the design and implementation of Machine Learning infrastructure for Voice AI products. Shape technical vision, mentor engineers, and collaborate on innovation.

Develop computer vision models and algorithms for perception in robotics. Implement pipelines for AI model training and deployment on robotic platforms.

The Senior ML Research Engineer will develop manipulation algorithms, motion planning models, and enhance robot learning stacks for high-DOF robotic tasks.

As a Senior Solutions Engineer, you will support customers in deploying ML applications, ensuring technical success, and enhancing their understanding of Flyte and Union Cloud.

The role involves designing and implementing machine learning models for prediction and motion planning in autonomous vehicles, driving cross-functional collaboration, and leading projects in a high-velocity environment.

Develop and optimize machine learning models and pipelines for autonomous vehicles, focusing on behavior prediction. Collaborate with teams, lead projects, and ensure high-quality implementations.

Develop and deploy machine learning models for agentic workflows, optimize AI systems for multimodal applications, and innovate fine-tuning techniques.

As a Machine Learning Engineer, you will build agentic systems for autonomous web navigation and complex task completion, integrating LLMs and reinforcing learning.

You will build and optimize data infrastructure for machine learning, design data pipelines, index systems, and ensure compliance in data handling.

As an AI/ML Engineer, you will develop and optimize AI solutions for renewable energy assets, collaborating with a skilled team to deploy algorithms in real-world projects.

Develop synthetic sensor simulation models and algorithms using machine learning techniques, analyze sensor data realism, and collaborate on map requirements.

Develop technologies for optimizing AI models in autonomous driving. Collaborate on parallel algorithms and influence compute platform architecture.

Develop synthetic sensor simulation methods using machine learning. Collaborate with teams to analyze sensor data realism and performance. Requires Python and ML expertise.

The Research Engineer will design and implement improvements for member-facing algorithms, focusing on large language models and quality evaluation metrics, leading initiatives in applied research and product development.