Machine Learning Jobs in Santa Clara, CA

As a Senior ML Infrastructure Engineer, you will design scalable architectures for ML, build robust data pipelines, manage GPU clusters, and drive improvements in CI/CD workflows while collaborating with cross-functional teams.

Develop and integrate AI/ML solutions for various autonomous platforms, optimizing models for edge devices, and collaborating with defense stakeholders.

The role involves designing and deploying risk models, enhancing credit and fraud models, and integrating advanced ML technologies. Responsibilities include collaboration, monitoring model health, and leading operational excellence.

Develop machine learning models for intelligent gameplay features, leverage real-world data for decision-making, and optimize data pipelines.

Develop computer vision and machine learning solutions, research algorithms, work with product teams to collect datasets, and balance research with production code.

Join Tenstorrent as a Senior Machine Learning Engineer responsible for developing AI application demonstrations and APIs. Experience in Kubernetes and AI frameworks is valued.

Seeking a Machine Learning Engineer for autonomous vehicle testing focused on scenario generation using LLMs/VLMs while ensuring AI-driven safety validation.

Lead the development of AI-driven machine learning solutions to optimize customer experience through personalization and recommendations, while guiding team technical direction.

Design and implement software optimizations for AI inference applications, collaborating with experts to influence hardware and software design.

The Forward-Deployed ML Engineer will develop AI weather models, manage external collaborations, and ensure integration with customer projects, translating technical work for non-technical stakeholders.

Develop robust AI/ML solutions for manufacturing, collaborating with scientists to build scalable infrastructure, optimizing ML systems, and ensuring code quality.

The Staff AI & ML Engineer at AlixPartners will design, implement, and deliver AI/ML solutions while leading teams and driving innovation across products.

Responsible for productizing software stack for AI compute engine; focusing on development, optimization, and scaling of AI deployment software, collaborating with hardware and software teams.

As a Senior Staff Software Engineer, you will develop and maintain AI deployment software, optimizing hardware-software co-design, and work closely with various experts to enhance infrastructure.

Develop and deploy machine learning models for lead scoring, implement NLP systems, and optimize model performance while collaborating with the backend team.

As a Senior AI Engineer, you will design and implement the orchestration layer for HP's AI operating system, with responsibilities including developing memory systems, integrating LLM APIs, and improving agent performance through experimentation.

As an AI Engineer, contribute to HP's intelligent operating system by building orchestration architecture for LLM agents, integrating APIs, and collaborating on innovative AI features.

The role involves advancing on-device AI optimization through techniques like quantization and pruning, collaborating with engineers, and developing efficient model deployment methods.

The ML Ops Engineer will manage machine learning lifecycle, infrastructure automation, monitoring, and compliance for AI systems to ensure operational reliability.

The Senior Machine Learning Engineer will enhance HP's retrieval systems and recommendation algorithms, focusing on AI-driven user interactions and system performance improvements.

Lead and develop a team of ML engineers and data scientists, guiding the creation of ML solutions with advanced techniques in AI, focusing on user-friendly systems.

Develop innovative perception autolabeling ML models for autonomous driving, leading projects and collaborating with multidisciplinary teams to enhance ADAS technology.

The Machine Learning Scientist will design experiments, analyze AI model behaviors, and develop metrics to improve model evaluation, collaborating closely with engineers and product teams.

Lead open-source research in AI, design experiments, develop methodologies, and analyze data to enhance model evaluation and transparency.

Lead the design and development of scalable, high-performance real-time data and API infrastructure to support AI applications. Mentor engineers, ensure system reliability, and collaborate across teams.