Machine Learning Jobs in Santa Clara, CA

As an Applied ML Validation Manager, lead a team to build frameworks for evaluating ML behavior against human driving expectations, working closely with various teams to integrate these outputs into validation processes.

Lead development of scalable ML infrastructure, focusing on compute for simulation, data labeling, and data generation. Collaborate with ML engineers, set technical roadmaps, ensure system reliability, and research advanced computing techniques.

The Senior ML Infrastructure Engineer will design, implement, and optimize computing platforms for simulation workflows, ensuring high reliability and performance. Responsibilities include leading technical decisions, collaborating with ML engineers, and enhancing system efficiency.

As a Manager in Data Science, you'll lead the development of machine learning models, partner with engineering and product teams, and analyze large datasets to enhance customer experiences and prevent fraud.

Seeking a seasoned Photonics Engineer to lead optical integration efforts in semiconductor testing, ensuring signal integrity and system reliability. Responsibilities include design, testing, and overseeing integration in high-volume manufacturing settings, along with mentorship and project management tasks.

Lead Safety Architect for autonomous vehicles, focusing on safety architecture, metrics, analysis, and collaborative processes for software delivery and safety standards.

Responsible for building AI frameworks for recommender systems on NVIDIA GPUs, developing product strategies, and collaborating with customers to enhance ML lifecycle products.

The role involves integrating machine learning and classical trajectory planners within safety frameworks for autonomous vehicles, focusing on architecture, planning, and control algorithms.

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

The Forward Deployed Research Scientist engages directly with AI labs to develop data strategies, fine-tune models, run experiments, and collaborate on publishing research, all in a fast-paced client-focused setting.

Develop and evaluate machine learning algorithms using time-series sensor data, integrate data pipelines with software engineering, and communicate technical information globally.

The role involves improving demand forecast accuracy, implementing ML models, and collaborating with various teams to analyze market trends.

The Staff Technical Program Manager will coordinate software development for XPENG’s AI-driven vehicles, optimize agile practices, and manage program risks while tracking KPIs and OKRs.

The Staff Applied Scientist will develop machine learning models for forecasting, collaborating with cross-functional teams to improve advertising campaigns, and drive model development using data.

Build and deploy scalable ML training and evaluation platforms, drive technical projects and architectural decisions, collaborate with partner teams, prioritize platform improvements, ensure reliability and performance, and mentor junior engineers.

Design, implement, and deploy scalable ML training and evaluation platforms. Own end-to-end projects, make architectural decisions, drive prioritization, collaborate cross-functionally, and mentor engineers to accelerate autonomous driving model development.

The role involves optimizing large-scale ML infrastructure for autonomous vehicles, conducting analyses, collaborating with teams, and improving system performance.

As a Senior Applied AI and AI Infrastructure Engineer, you will manage AI projects, deploy infrastructure, mentor junior engineers, and apply AI for chip design.

Lead Applied AI product initiatives for mobile games by identifying gameplay opportunities, defining AI-driven roadmaps, translating between game design and ML teams, setting mixed technical and game success metrics, and partnering with central tech teams to deploy ML features that improve fun and retention.

The Senior Neural Graphics Scientist will define NVIDIA's Neural Graphics strategy, pioneer neural shading techniques, connect research to products, drive AI innovations, and influence hardware design.

The Machine Learning System Software Architect will lead high-performance machine learning software architecture, collaborating with teams to optimize AI solutions, evaluating architecture for performance, and driving innovation in AI training systems.

Manage complex programs for developing customer-facing geospatial technologies. Oversee the program lifecycle, coordinate with teams, and ensure successful deployment.

Develop ML-first behavior modules for predicting future motions of road users. Collaborate with perception and planning teams to enhance autonomous systems.

Conduct research on AI and robotics, focusing on reinforcement learning, and collaborate on publications and algorithm deployment.

The ML Perception Software Engineer will develop perception modules for autonomous vehicles, focusing on machine learning and computer vision to enhance navigation capabilities.