Machine Learning Jobs in Santa Clara, CA

Lead the Seller User Experience team, focusing on enhancing customer satisfaction through innovative technology solutions and user feedback. Collaborate with stakeholders and mentor teams to achieve superior user experiences.

You will design and implement high-performance software while applying machine learning techniques to complex problems in electronic design automation.

Lead strategic ISV partnerships to integrate NVIDIA software and SDKs into partner data platforms. Drive technical and GTM alignment, influence product strategy, recruit and lead cross-functional teams, promote NVIDIA solutions to architect and developer communities, and surface partner needs to internal product and engineering teams.

Design and develop scalable, high-performance data and API infrastructure for real-time processing. Mentor engineers and collaborate with teams to enhance AI model evaluations.

Responsible for designing experiments to evaluate AI models, developing evaluation methodologies, analyzing performance data, and collaborating on production insights.

Designs, builds, and evaluates language models for AI security products. Responsibilities include dataset curation, preprocessing, LLM experimentation, safety and robustness evaluation, dashboards, knowledge graphs, model fine-tuning, production integration, monitoring, CI/CD, and ML tooling. Collaborates with researchers and data scientists to automate quality assurance and guardrails while delivering reliable, scalable, and interpretable models.

Lead execution of Product Engineering AI and automation initiatives across photonics products. Build and deploy reusable AI/automation tools, transform engineering data into AI-ready systems, and drive cross-functional adoption to improve development, qualification, manufacturing, and reliability processes.

Develop and maintain Android applications for embedded devices; prototype and debug on hardware (Raspberry Pi, NVIDIA); work with Yocto build systems, Qt/QML, and Git/Stash. Preferred experience with web frameworks, iOS, AR/VR, and machine learning. Collaborate with team, communicate effectively, and support embedded graphics/media and RTOS environments.

As a new engineer at Cerebras, you'll learn their platforms, focusing on programming the Wafer Scale Engine, kernel development, and system performance modeling.

Design scalable data analytics platforms, make architectural decisions, collaborate with analysts, mentor developers, and assess technologies for a Big Data Platform.

The CTO will lead Fathom's technical strategy, focusing on AI governance, building partnerships, defining standards, and advancing AI safety practices.

The role involves developing AI applications for VLSI design using machine learning and related technologies. Duties include infrastructure design, AI solution implementation, collaboration with teams, and maintaining design databases.

Manage and grow sales strategies and customer relationships for proteanTecs in the semiconductor industry, ensuring long-term success by aligning solutions with customer needs.

The Director of Application Engineering leads a team of engineers, manages customer support, trains clients on tools, and collaborates with R&D to enhance product features.

As a Software Engineer, you'll develop software solutions for semiconductor equipment, lead projects, troubleshoot complex issues, and collaborate with customers on requirements.

As Director of AV Product Engineering, you will manage product engineering, develop autonomous vehicle capabilities, and lead multiple teams to ensure alignment with company objectives while fostering technical growth and innovation.

Conduct research on reinforcement learning and robotics, collaborate with scientists on publications, and contribute to next-generation autonomy technology.

The Research Intern will assist in projects related to robotics, simulation, and data processing, while collaborating on research publications with scientists and engineers.

Conduct research on autonomous systems, collaborate with scientists on publications, and improve robotic models using large-scale data.

Research Intern will conduct studies on 3D vision topics and collaborate with scientists for research publications related to autonomous driving and robotics.

Lead the design, implementation, and deployment of scalable ML infrastructure for autonomous driving. Drive technical projects, mentor others, and collaborate with teams to enhance ML workflows.

Lead design, training, and evaluation of multi-modal ML perception models (camera, lidar, radar) for fallback autonomy. Define metrics, curate datasets, implement training and optimized inference pipelines for on‑vehicle constraints, and integrate models into production. Partner with safety, systems, and product teams for validation, verification, and deployment. Mentor engineers and promote ML and software engineering best practices.

Lead AI/ML safety engineering for Level 4 autonomous vehicles. Define SOTIF and functional safety strategies, derive requirements for learned systems, design runtime safety monitors and OOD detectors, assess dataset coverage and bias, analyze ML failure modes, and build evidence-backed safety cases. The role requires collaboration across perception, prediction, planning, systems, and safety engineering teams, with onsite work five days per week in Santa Clara, California.

Develop and deploy machine learning planning algorithms for autonomous trucks. Own the full ML lifecycle, including data curation, feature engineering, training, evaluation, deployment, monitoring, and improvement. Design trajectory and behavior-planning models, safety guardrails, validation pipelines, and performance metrics. Investigate failures and edge cases, optimize inference, and collaborate with perception, prediction, mapping, runtime, and systems teams to deliver reliable production systems.

Lead development of real-time machine learning and computer vision systems for robotic-assisted surgery. Design and deploy deep learning models for surgical scene understanding, segmentation, detection, 3D reasoning, and probabilistic inference. Own models from research through production integration with C++ and embedded robotic platforms, optimizing latency and reliability. Define clinically meaningful validation methods, collaborate with surgeons and engineering teams, mentor colleagues, and contribute to patents and regulated medical-device development.