Machine Learning Jobs in San Jose, CA

As a Principal Associate Data Scientist, you'll build AI and machine learning models to analyze data, partner with teams, and deliver impactful products.

Responsible for developing AI/ML solutions, managing teams, understanding product requirements, and creating data processing pipelines to enhance enterprise services.

The role involves full product management scope for CPQ Pricing, focusing on strategy, execution, and stakeholder collaboration to enhance AI-infused pricing workflows.

Lead a cross-disciplinary design team to drive product design strategy, enhance user experiences, and leverage AI tools. Collaborate with other departments to ensure data usability and design excellence.

The role involves building and optimizing large language models for the ServiceNow platform, requiring AI/ML expertise and collaboration with various stakeholders.

As a Principal Machine Learning Engineer at Zscaler, you will lead AI/ML projects, optimize systems, and collaborate on cybersecurity solutions while mentoring engineers.

The role involves building machine learning models, data analysis, and partnering with various teams to enhance customer experiences in financial services.

The Investment Director will lead venture capital investments, focusing on AI initiatives, strategic relationships, and cross-functional coordination in AI/ML execution while mentoring team members.

The role involves developing LLM applications for automated silicon design, optimizing models, curating datasets, and collaborating with other experts to integrate LLMs into EDA workflows.

The role involves leading corporate venture capital initiatives, sourcing deals, managing investments, and collaborating on AI and ML projects. It requires mentoring and strategic communication with senior executives.

Lead the transformation of enterprise security through AI, redesigning operations for efficiency, implementing analytics for risk identification, and unifying security systems into an AI-enabled architecture.

In this role, you will develop AI foundation models, perform applied research, collaborate with cross-functional teams, and leverage advanced technologies to enhance customer experiences in banking.

Lead game analytics teams to transform player data into strategies for enhancing engagement and revenue across key titles. Manage projects, mentor analysts, and collaborate with product leaders for decision-making.

As a Staff Machine Learning Engineer, you will design and develop VoIP infrastructure and integrate LLMs into voice platforms while enhancing operational practices.

Design and develop AI/ML solutions, focusing on scalable software and user experience, while collaborating across teams to integrate generative AI technologies.

In this role, you will design, develop, and implement VoIP infrastructure, integrate LLMs into voice platforms, and enhance AI-driven workflows while collaborating with various engineering teams.

The role involves developing networking solutions, conducting technical meetings, and collaborating with customers to drive AI hardware implementations.

Design and build a scalable failure-attribution framework for heterogeneous CPU/GPU clusters: collect high-fidelity telemetry, implement low-overhead tracing, automate root-cause classification (hardware, software, environment), and enable proactive resiliency measures like migration or checkpointing.

Design and implement developer tooling to debug, profile, and analyze next‑gen graphics and neural-rendering workloads. Collaborate with research and architecture teams, write high-performance C/C++ code, perform design and peer reviews, document requirements, and work with QA to validate features.

The Research Scientist will design networks optimized for AI, create algorithms for decision-making in GPU clusters, and develop innovative networking technologies.

Interns will work on real-world projects in hardware and software engineering, engage with experienced mentors, and apply academic knowledge to tackle challenges.

We are seeking a software developer for our Virtuoso place and route infrastructure team, applying advanced techniques in machine learning and computer science.

Lead technical engagements with customers on performance optimization for AI and HPC applications, build demos, and conduct workshops.

Design and implement algorithms and tools for chip-level placement, reshaping, and global routing. Develop computational geometry, placement, routing and graph-optimization solutions, apply machine learning for design space exploration, extend GUIs for debugging/visualization, and collaborate with design teams to deploy high-performance C++ tools impacting next-generation AI chip physical layouts.

Responsible for defining and delivering advanced planning and controls technology for NVIDIA's self-driving software, collaborating with teams to achieve project goals.