Machine Learning Jobs in Santa Clara, CA

The role involves developing software for silicon testing, applying graph and ML techniques, and collaborating with teams on innovative solutions.

The job involves developing machine learning models for climate change, leveraging neural reasoning and data analysis to provide insights in sustainability and finance.

As a Senior MLOps Engineer, you will optimize machine learning models for performance and scalability, collaborate with R&D engineers, and implement CI/CD pipelines.

As a Senior Software Engineer, you will build scalable machine learning systems, mentor junior developers, and collaborate with data scientists and product owners.

You will build a search and assistant product, improve personalization, train models, and write robust code while mentoring junior engineers.

Develop and train advanced generative models for synthetic data generation to enhance Zoox's autonomous driving capabilities. Collaborate across teams and validate models using real-world scenarios.

Responsible for architecting high-performance machine learning silicon, collaborating with software and design engineers, and driving innovation in AI hardware solutions.

The role involves developing neural model architectures and optimizing ML systems for performance on TPU and GPU, focusing on efficiency and scalability in autonomous driving applications.

The Staff Machine Learning R&D Engineer will innovate machine learning algorithms for spatial computing, collaborate with teams, and translate research into production solutions.

The role involves enhancing AI/ML infrastructure for efficiency, collaborating with teams to address deficiencies, and optimizing resources.

Develop and implement online mapping models and algorithms for robotics, focusing on machine learning and data management within uncertain environments.

As a Staff Machine Learning Engineer, you will enhance Coupang's search and discovery algorithms using ML, DL, and NLP to improve product relevance and user interaction.

Lead initiatives in model-based autonomous driving, developing end-to-end driving models and collaborating with cross-functional teams. Mentor senior engineers and influence technical direction.

Drive machine learning innovations for search and discovery, addressing defects and building models to enhance customer experience and business metrics.

The Principal Platform Engineer will own platform as a product, manage ML platform components, and enhance developer experiences while optimizing performance and scaling infrastructure.

This role leads the AI/ML Platforms team, driving the strategy and development of AI solutions and cloud migrations while collaborating with cross-functional teams.

The role involves developing AI-driven solutions for cybersecurity, focusing on machine learning pipelines, threat detection, and mitigation strategies against sophisticated cyber threats.

As a Multimodal Machine Learning Engineer, you'll design AI solutions for multimodal content, develop technologies for automated content generation, and advance AI-driven products.

Design and develop machine learning infrastructure, enhancing core components for model training, monitoring, and serving. Collaborate with ML engineers on robust pipelines.

As a Machine Learning Engineer, you'll develop and optimize recommendation systems, focusing on user behavior modeling, data pipeline development, and feature engineering.

As a Senior Machine Learning Engineer, you'll enhance Moveworks' NLU and AI capabilities, improve user experiences, and develop innovative solutions using machine learning and advanced NLP techniques.

Design and develop advanced search-based question answering systems using traditional and generative AI techniques. Lead a team, mentor engineers, and drive innovations.

Design, develop, and deploy advanced causal Marketing Mix Models to guide marketing budget decisions and business growth at Adobe.

Design and implement distributed cloud GPU training for ML, build end-to-end pipelines, collaborate on data problems, and uphold ML best practices.

Lead software engineer focusing on optimizing ML models for embedded systems, improving performance and efficiency in production environments.