Machine Learning Jobs in Santa Clara, CA

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.

The Senior ML/AI Engineer will enhance developer productivity for AV engineers at GM by designing, implementing scalable, reliable systems and mentoring team members.

Lead design, build, and operate AIOps and observability platforms (metrics, logs, traces, alerts, dashboards). Define roadmap and standards, collaborate with teams, mentor engineers, and implement ML/LLM-based anomaly detection, forecasting, root-cause analysis, and agentic debugging across large-scale cloud, on-prem, and bare-metal environments.

Develop and validate advanced driver assistance and autonomous driving systems, ensuring compliance with regulatory requirements while mentoring junior engineers.

Lead end-to-end supply chain business transformation initiatives—defining strategy, redesigning processes and operating models, translating requirements into solutions, and partnering with IT, engineering, data and analytics teams to deliver scalable digital capabilities, AI/ML adoption, and measurable operational improvements across planning, logistics, manufacturing, repair, returns, and customer operations.

Define and position datacenter GPU products for AI, ML, and HPC workloads (especially LLMs). Identify customer needs, translate into product value propositions, lead cross-functional go-to-market planning, and create sales collateral while coordinating with engineering, operations, and field teams.

Lead research on generative world models and synthetic data to improve training, evaluation, and generalization of end-to-end autonomous driving systems. Prototype and develop algorithms, collaborate with research and product teams to scale advances into production, define research direction and roadmaps, and drive technology transfer for safe Level 4 autonomy.

Support compact device modeling for advanced Intel process technologies (FinFET/GAA). Develop and validate transistor compact models (BSIM-CMG), use extraction tools and simulators, analyze data with Python, apply ML for model development, collaborate across teams, and benchmark device and circuit performance including layout-dependent and self-heating effects.

Develop, test, and document embedded software and firmware for an SoC-based sensor/BLE board. Implement multi-channel data acquisition, optimize signal-processing and proprietary algorithms, create BLE/server communications protocols, build device drivers, perform testing, and produce documentation.

Lead design, build, and operate scalable observability systems for distributed cloud and on-vehicle environments. Contribute code and reviews, create technical designs, build tooling to collect observability signals, run PoCs for new tools, partner with engineering teams, define SLIs/SLOs, guide roadmap decisions, and mentor engineers to improve developer productivity and reliability.

Lead data science research and develop scalable ML models, audience segmentation, propensity and recommender systems for marketing and eCommerce. Cleanse and integrate large disparate datasets, apply causal inference and A/B testing, define KPIs, ensure data governance and privacy, and communicate insights to product, sales, and marketing stakeholders to drive revenue and product improvements.

The Technical Program Manager will lead software programs, collaborate with multiple teams, manage dependencies, and drive product delivery to improve engineering velocity and transparency.

As a Senior Machine Learning Scientist, you will develop methodologies for advertising-related challenges, utilizing deep learning and statistical techniques for optimization and experimentation.

Architect and lead the development of a state-of-the-art inference platform focusing on low latency and scalability for advertising. Oversee performance optimization and collaborate with cross-functional teams.

Lead end-to-end product development for SaMD neurodiagnostics (EEG) products. Define vision, write requirements and acceptance criteria, manage backlog and releases, integrate AI features, ensure FDA and global regulatory compliance, drive VOC and competitive analysis, and coordinate cross-functional execution from design through verification and launch.

Lead enterprise DevOps, SRE, platform engineering, and cloud operations strategy. Modernize CI/CD, infrastructure automation, and cloud-native platforms; embed DevSecOps; apply AIOps/MLOps and generative AI for automation; measure reliability (SLOs/SLAs); manage budgets, vendors, and global engineering teams to improve resilience and delivery.

Lead cross-functional compiler software programs from concept to delivery, coordinating global teams, tracking risks and schedules, and improving development processes. Present status to executives, drive Agile and Waterfall projects, resolve technical/resource conflicts, and implement process and tool automation to ensure timely product releases.

Lead development and operation of CI platform components (RBE, FUSE) to enable scalable build, test, and developer workflows. Collaborate across teams, own projects end-to-end, drive engineering best practices, mentor engineers, perform design/code reviews, and support integration of internal tools with the FUSE-based file system to improve developer productivity for AV and ML workloads.

As a Research Scientist and Engineer at Collinear, you will create AI simulation environments, develop evaluation systems, and enhance real-world model performance through rigorous data-driven approaches.

Lead Collinear's research direction across evaluation, simulation, and post-training ML methods while managing a high-caliber research team. Influence customer outcomes through applied research.

Drive planning and execution of multiple software and ML workstreams, manage cross-functional dependencies, gather requirements, track schedules, support development-to-deployment, and improve processes to deliver customer product releases.

As a Senior Machine Learning Engineer, you will develop advanced machine learning and deep learning models and platforms for optimizing advertising performance and conduct complex experiments.

Develop and optimize lightweight machine learning models for edge AI applications, integrating into production systems and mentoring junior engineers.