Artificial Intelligence Jobs in Santa Clara, CA

Leads Altera’s AI transformation of hardware design by defining AI/ML strategy, deploying tools across design, verification, and implementation workflows, building data and evaluation foundations, and measuring productivity impact. The role requires deep semiconductor and EDA expertise, hands-on ML/LLM experience, cross-functional influence, vendor evaluation, stakeholder engagement, and mentoring without direct reports.

Defines the technical vision and architecture for NVIDIA’s next-generation autonomous driving stack, integrating classical safety systems with learning-based autonomy. Leads engineering teams across prediction, planning, control, decision-making, and safety; oversees productionization of end-to-end driving pipelines and foundation models; and partners with research teams to bring robotics, embodied AI, and generative AI advances into scalable autonomous vehicle systems.

Advise Product, Engineering, Design, Marketing, and business teams on privacy, data protection, accessibility, consumer protection, copyright, contracts, IP, and emerging AI and autonomy technologies. Lead compliance, safety, patenting, invention harvesting, product integration reviews, and legal process development. Translate legal guidance into actionable product workflows, manage complex cross-functional projects, monitor regulatory developments, review external-facing documents, and support M&A transactions.

Lead and grow strategic partnerships across the Physical AI stack (robotics, simulation, autonomous systems). Drive joint product integrations, co-innovation, go-to-market motions, co-sell opportunities, and partner-aligned roadmaps with NVIDIA and key platform/OEM partners. Influence Product and Engineering requirements, execute quarterly business plans, and represent CoreWeave at industry events to accelerate revenue and market adoption.

Lead F5’s global product design organization and define the UX/UI vision across platform products. Develop scalable design strategies, unified design systems, and AI-enabled user experiences. Partner with product, engineering, AI, marketing, and analytics teams to improve accessibility, personalization, usability, adoption, retention, and customer satisfaction. Mentor and scale cross-functional design teams while balancing executive-level strategy with hands-on guidance and timely execution.

Leads enterprise FP&A, including P&L consolidation, annual operating planning, forecasting, actuals reporting, scenario analysis, and board and earnings preparation. Owns the FP&A technology and AI roadmap, automates executive decision products, improves financial workflows, and develops a modern finance organization. Partners with senior leaders across Finance and the broader business to deliver strategic insights and drive aligned financial decisions.

Own and grow strategic partnerships with cloud providers, semiconductor foundries, data and compute providers, and lighthouse customers. Lead co-selling initiatives, support product architecture decisions, structure complex commercial and co-development agreements, and identify opportunities across product, R&D, and go-to-market teams. Translate technical and business needs into partnership strategy for an AI-powered chip design platform.

Lead financial modeling, valuation, diligence, and transaction execution for acquisitions, venture investments, and strategic partnerships. Build DCF, comparable company, pro forma, and synergy analyses; coordinate cross-functional diligence; evaluate markets and targets; support deal structuring, negotiations, and executive decision-making. Maintain deal pipelines and infrastructure, prepare investment memos and transaction materials, guide associate-level support, and help develop AI-enabled deal processes and market intelligence capabilities.

Supports FP&A and enterprise analytics by developing scalable Power BI reporting, financial models, dashboards, and automated processes. Analyzes financial and operational datasets to identify trends, risks, and opportunities; improves forecasting, budgeting, and recurring reporting workflows using Excel, Python, SQL, Power Automate, and Microsoft platforms. Collaborates with finance, data engineering, IT, and business stakeholders, trains users, maintains governance standards, and contributes to the Pigment planning platform. Evaluates AI-enabled tools to improve reporting efficiency, data quality, and decision-making.

Design and build scalable AI platform capabilities to enable multi-step GenAI workflows, model execution, and integrations. Implement backend services, execution infrastructure, APIs, and observability to support production GenAI experiences across sales and product teams. Collaborate with AI engineers, data scientists, and product partners to turn AI use cases into reliable, extensible platform features.

Lead technical vision and architecture for ML-driven trajectory generation in autonomous vehicles. Build and deploy scalable training pipelines, integrate models into real-time safety-critical onboard systems, mentor senior engineers, drive cross-functional initiatives, and move solutions from research to production using simulation and large-scale datasets.

Develop and evaluate ML and perception models for future sensing and autonomous driving. Work on detection, tracking, classification, sensor fusion, training pipelines, validation, robustness metrics, and integrate models into onboard systems while collaborating with cross-functional teams.

Lead end-to-end ML and perception efforts for future sensing in autonomous vehicles: design sensor architectures, multi-modal fusion, model development, metrics, simulation-driven evaluation, system integration, and production readiness while mentoring engineers and building scalable data and training infrastructure.

Own strategic territories and close net-new enterprise software deals. Lead value-based sales cycles from discovery through proof of value, negotiation, and close; build executive relationships; develop account strategies; maintain Salesforce pipeline and forecasts; partner with alliances teams; and advise customers on supply chain resilience, risk, and compliance.

Develop production-grade multimodal AI systems for L3/L4 autonomous vehicles. Build sensor-fusion and spatiotemporal world models combining camera, LiDAR, radar, navigation, and vehicle-state data. Create multitask models for road understanding, occupancy, perception, prediction, and planning; develop scalable training and evaluation pipelines; investigate foundation-model approaches; optimize models for real-time NVIDIA hardware; and collaborate across AV engineering teams to deploy robust systems.

Supports the GTM Lead and founders across sales, growth, and content. Responsibilities include creating technical content for AI products, running growth experiments, supporting outbound initiatives, building the sales funnel, communicating with technical buyers, and collaborating with engineering in an early-stage environment.

Build Lingopal’s go-to-market motion for its evolving AI agent platform. Develop positioning, target accounts, outbound strategy, sales processes, and pricing inputs. Own enterprise sales from prospecting through discovery, pilots, and closing across customer-support-heavy enterprises and scaling AI-agent companies. Engage senior buyers including Chief AI Officers, COOs, and CTOs, while feeding market insights back into product strategy.

Build Weave’s AI-native lead generation infrastructure from scratch, including agentic workflows, automation, lead sourcing, enrichment, qualification, targeting models, and multichannel campaigns. Partner with account executives and RevOps to define lead quality, maintain HubSpot data hygiene, improve handoffs, and connect lead quality to pipeline conversion. Run data-driven experiments to optimize engagement, conversion rates, and pipeline contribution.

Architect, build, deploy, and operate production-grade AI agentic systems and workflows. Responsibilities include backend and full-stack development, agent orchestration, workflow state, retrieval, memory, approvals, failure recovery, data architecture, enterprise integrations, cloud infrastructure, observability, security, and scaling. The role establishes reusable engineering patterns and partners with users to deliver reliable AI products, while addressing production issues involving model behavior, permissions, latency, cost, and consistency.

Own the roadmap and delivery of AI infrastructure resilience platform features, including telemetry, health checks, attribution, observability APIs, and deployment experiences. Translate developer needs into product strategy, collaborate with engineering on architecture and execution, engage open-source contributors through GitHub, and align product, marketing, field, and engineering teams. The role requires deep technical expertise in AI infrastructure, Kubernetes, developer platforms, or related systems, plus extensive product management or engineering experience.

Lead editorial vision and content strategy for a technical AI research lab. Develop the editorial voice, calendar, content engine, long-form and short-form content, multimedia storytelling, and owned channels. Translate complex research into credible, accessible communications for technical and general audiences. Partner with engineers, researchers, communications, and product teams on launches and flagship reports; manage a social media manager, build a freelance writing team, and track content performance metrics.

Secure AI and cloud-native applications by embedding controls into the Secure SDLC, CI/CD pipelines, Kubernetes environments, APIs, and software supply chains. Lead threat modeling, secure design reviews, vulnerability remediation, container hardening, runtime policy enforcement, and AI/ML workload protection. Partner with engineering teams to establish secure coding standards and improve enterprise security posture.

Lead RTL development and microarchitecture for an AI-enabled RISC-V CPU core, including vector and matrix engines. Own functional features, performance, power, area, timing, and physical design considerations. Develop specifications, optimize RTL, support verification, and collaborate on CPU modeling, design verification, and SoC integration. The role requires deep expertise in high-performance CPU architecture, cache and memory subsystems, SystemVerilog or related HDL technologies, and advanced processor design.

Own and ship agentic AI products for Uber’s customer experience platform. Define product strategy, roadmaps, requirements, success metrics, and tradeoffs while partnering with Engineering, Data Science, Design, User Research, and Operations. Improve agent quality through evaluation, experimentation, simulations, observability, debugging, and human feedback. Use customer insights and performance data to iterate on AI-powered experiences and drive cross-functional execution from discovery through launch.

Build and operate production machine learning and backend systems for AI data and evaluation products. Own a business vertical end to end, from identifying opportunities and setting direction to delivering revenue-generating products. Partner with customers, product managers, and engineers; drive adoption, customer value, and execution quality. Apply machine learning across multimodal data, LLM evaluation, physical-world data, robotics, audio, video, and related domains.