Machine Learning Jobs in Sunnyvale, CA

Seeking a PhD research intern to develop algorithms for robot manipulation, working on AI models and collaborating in a robotics startup environment.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

Lead the design and implementation of scalable AI systems focusing on large language models and speech technologies, while providing technical leadership and mentoring.

As a Machine Learning Research Scientist, you will develop advanced algorithms for behavior planning and prediction for autonomous vehicles, focusing on machine learning techniques to solve real-world challenges in trajectory generation and motion planning.

The role involves bridging machine learning and systems engineering to enhance autonomy performance by optimizing data quality and developing frameworks for synthetic data in autonomous systems.

As a Senior ML Infrastructure Engineer, you will design scalable architectures for ML, build robust data pipelines, manage GPU clusters, and drive improvements in CI/CD workflows while collaborating with cross-functional teams.

As a Senior Machine Learning Engineer, you will own the ML stack, develop generation systems, improve quality, collaborate cross-functionally, and build data pipelines.

The Machine Learning Engineer will build and scale ML infrastructure, drive model performance, and ensure reliability while collaborating with various teams to optimize feature engineering pipelines and champion best practices.

Lead the design and implementation of GPU compute clusters for deep learning and high-performance workloads, manage large-scale systems and ensure efficient resource utilization.

Optimize machine learning models for embedded environments, focusing on performance, efficiency, and deployment strategies across various platforms.

The Machine Learning Engineer role at Wayve focuses on leading initiatives in model-based autonomous driving, involving the development and delivery of ML-driven behaviors, collaboration across teams, and mentoring other engineers.

The role involves building and evolving ML inference infrastructure for simulations, ensuring reliability and a high-quality user experience for ML model deployment and serving.

As a Senior Machine Learning Engineer at Unity, you will modernize infrastructure, build intelligent systems using LLMs, and mentor teammates.

The role involves designing large-scale offline platforms for ML training, developing data pipelines, ensuring scalability and performance, and integrating orchestration systems.

The intern will profile, optimize, and automate training processes for BEV models, developing custom kernels and leveraging LLMs for performance improvements.

As a Senior MLOps Engineer, you will optimize machine learning models for performance and scalability, collaborate with R&D engineers, and implement CI/CD pipelines.

As an ML Engineer at Luma AI, you will design high-performance model serving pipelines, manage GPU resources, and optimize CI/CD for large-scale AI systems.

Lead the navigation ML workstream for autonomous driving systems, overseeing model training and deployment, defining technical direction, and mentoring junior engineers.

You will create large datasets and training recipes, develop methods for data mining, create scalable infrastructure solutions, and collaborate with ML infrastructure teams.

Work on vision-language model development and infrastructure: improve VLM understanding, OCR and function-calling workflows, fine-tuning recipes, evaluation and robustness, and optimize training/serving pipelines. Own end-to-end projects from experiments to production-ready code, collaborating on scale, cost, and reliability.

Build and scale the infrastructure layer for visual intelligence: optimize VLM inference and GPU serving, design multimodal APIs and structured outputs, ensure scalable backend systems, reliability, observability, CI/CD, and developer experience. Drive 0→1 product work with strong testing discipline, schema validation, and performance optimization.

Lead RTL development and microarchitecture for an AI-enabled RISC-V CPU core, including vector and matrix engines. Define features, optimize performance/power/area, support verification and simulation, collaborate with CPU modeling and physical design teams, and ensure design meets timing, reliability, testability, and power goals.

Design and specify microarchitectures and high-performance execution units for ML accelerators. Translate researcher requirements into hardware features, optimize power/area/performance, and collaborate with verification teams to ensure functional correctness and performance.

As a Staff ML Software Engineer, you will lead the development and deployment of machine learning applications, leveraging your expertise to drive software architecture decisions, maintain cloud infrastructure, and collaborate within a small, agile team focused on geospatial challenges related to climate change.

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.