Machine Learning Jobs in Santa Clara, CA

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

Lead an ML Platform engineering team building large-scale GPU cluster architecture, training and inference orchestration, and performance optimization. Own design, scaling, scheduling, networking, and resource management while partnering with research and stack teams to accelerate production deployment and drive hiring and mentorship.

The Senior Software Engineer will innovate in AI, lead software development lifecycle, design microservices, mentor peers, and ensure engineering excellence.

Lead end-to-end silicon diagnostic pipeline using AI/ML to analyze scan failures and process data, build models for failure classification and predictive yield, orchestrate AI-based EDA tools, and drive cross-functional root-cause analysis to improve yield and time-to-market.

The role involves developing and maintaining machine learning models for robotics, creating training and deployment pipelines, and collaborating on product needs.

The Senior Machine Learning R&D Engineer will innovate in spatial computing, develop ML algorithms, process 3D data, and collaborate with teams to enhance Matterport's platform.

As a Senior Software Engineer at NVIDIA, you will design and implement inference software optimizations for AI applications using TensorRT, collaborating with deep learning experts to influence hardware and software design.

The Performance Engineer - Inference will optimize model inference speed and throughput, debug low-level kernel performance, and develop tools to visualize performance data.

Design and implement system-level debugging, validation, and observability platforms. Build automated anomaly detection, visualization and analysis tools, and frameworks for failure classification and regression detection. Extend compilers, runtimes, and instrumentation for advanced profiling. Improve bring-up and low-level debug workflows, partner cross-functionally across hardware, firmware, compiler and runtime teams, lead high-impact initiatives, and support incident response and long-term corrective actions.

Develop and implement image processing and machine learning algorithms, collaborate with engineers, and demonstrate algorithm performance for semiconductor process development.

Lead development of scalable molecular dynamics pipelines, integrating physics-based models with machine learning frameworks to enhance molecular engineering and experimentations.

The ML Research Scientist will design Bayesian optimization frameworks, collaborate with lab scientists, and integrate ML models with experimental data.

The role involves designing de novo frameworks for molecular engineering, collaborating across teams to optimize data-driven biological experiments and integrating ML models with experimental systems.

The Senior Machine Learning Engineer will design and build scalable ML systems, mentor junior engineers, oversee ML model productionization, and ensure overall engineering best practices are followed.

Support data preparation, labeling, training workflows, and validation processes for machine learning systems. Execute and monitor ML pipelines, organize datasets, and evaluate model performance.

Develop leading machine learning frameworks for NVIDIA Earth-2, validate applications, and implement new ideas in deep learning for weather and climate AI.

Develop algorithms and optimizations for inference and compiler stack, enhance performance metrics, collaborate with hardware teams, and publish work on novel approaches.

Seeking Machine Learning Systems Engineers to build end-to-end 3D native ML systems, focusing on training and inference challenges.

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

The Machine Learning Scientist will lead open-source research, design experiments, develop novel methodologies, and analyze large-scale data to advance AI model evaluation and transparency.

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.

Lead and build a research-focused ML team to develop post-training/RL, dataset curation, LLM pretraining, and sparsity techniques; adapt algorithms to Cerebras hardware, run systematic model evaluation, and collaborate with internal teams and external partners to drive production deployments and hardware/software co-design.

Design and develop Bird’s Eye View fusion models for autonomous driving using multimodal sensor inputs like LiDAR, focusing on performance, robustness, and scalability.

The Senior ML/RL Engineer will develop behavior models, implement RL algorithms focusing on safety, design reward functions and optimize training environments while collaborating across teams.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.