Machine Learning Jobs in San Jose, CA

The role involves developing AI/ML models, engaging in product lifecycle management, and implementing ML-Ops practices for Adobe's Document Cloud customers.

Join Adobe's Search and Discovery team as an Applications and Machine Learning Engineer, focusing on building scalable search solutions and algorithms for various Adobe products.

Lead the design and deployment of ML systems to enhance customer experiences, mentor engineers, and drive AI initiatives, collaborating closely across teams.

You will build frameworks for LLM-powered agents, design reinforcement learning approaches, lead development of scalable evaluation systems, and mentor other engineers while writing robust code for enterprise-grade assistants.

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

Design, build, and optimize high-performance network infrastructure for AI/ML operations, focusing on InfiniBand and Ethernet fabrics, while ensuring peak performance and network security.

As a Machine Learning Support Engineer, you will address customer product issues, provide proactive guidance, and propose solutions to help clients succeed with Labelbox products.

As an AI Research Intern, design and implement AI algorithms to enhance semiconductor processes, develop proof-of-concept solutions, and collaborate with teams while also conducting publishable research.

Design advanced AI algorithms to enhance silicon and systems development, collaborate with teams for proof-of-concept, and publish research findings.

As a Senior Site Reliability Engineer, you'll manage and optimize HPC cluster operations, develop automation, troubleshoot issues, and support ML/research teams while ensuring smooth infrastructure operations.

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

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.

Lead the development of an AI-powered analytics platform focusing on data systems, ML, and natural language interfaces to enhance cloud security.

Develop and optimize machine learning compilers for autonomous driving models on general purpose GPUs, enhancing performance and efficiency.

The role involves co-designing hardware instructions and optimizing transformer model operations for AI chip performance, collaborating across software and hardware teams.

The role involves developing ML models for search and recommendation systems, managing AI technologies, and enhancing user experiences across Adobe products, requiring a strong background in AI, ML, and extensive industry experience.

The Senior ML Engineer will develop and implement ML models, collaborate with teams, and enhance AI workflows while guiding junior members.

Research, design, and deploy advanced ML models for video understanding and multimodal AI, focusing on enhancing video AI systems for enterprise use.

As a Machine Learning Intern at Ema, you will work on building and deploying machine learning models, analyzing datasets, and collaborating with senior engineers in a fast-paced startup environment.

Lead the design and strategy of an ML inference platform for AI security, providing mentorship and driving optimization in a collaborative environment.

As a Senior Staff Machine Learning Engineer, you'll develop AI-driven solutions to optimize customer experiences through advanced ML frameworks, focusing on recommendations and personalization.

Lead the design, development, and implementation of advanced machine learning models, collaborating with teams to enhance services through AI/ML solutions.

Responsible for architecting and optimizing ML pipelines, training ML models for business solutions, and providing technical leadership for deployment of ML systems.

The AI/ML Engineer will develop intelligent features using LLMs and traditional ML, build APIs, collaborate across teams, and optimize performance.