Machine Learning Jobs in San Jose, CA

Lead diverse technology projects and a team to create solutions for regulatory needs, leveraging distributed microservices and collaboration with product managers.

As a Principal Machine Learning Engineer at Zscaler, you will lead AI/ML projects, optimize systems, and collaborate on cybersecurity solutions while mentoring engineers.

The role involves building machine learning models, data analysis, and partnering with various teams to enhance customer experiences in financial services.

The Fraud Program Manager will enhance the fraud risk management program, develop monitoring metrics, manage anti-fraud policy updates, and collaborate across teams to ensure compliance and effectiveness in fraud prevention.

The Global Head of Sanctions will lead Block's sanctions compliance program, manage escalations, regulatory reporting, and engaging with external agencies while developing and implementing sanctions policies.

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

The role involves developing LLM applications for automated silicon design, optimizing models, curating datasets, and collaborating with other experts to integrate LLMs into EDA workflows.

In this role, you will develop AI foundation models, perform applied research, collaborate with cross-functional teams, and leverage advanced technologies to enhance customer experiences in banking.

The role involves leading corporate venture capital initiatives, sourcing deals, managing investments, and collaborating on AI and ML projects. It requires mentoring and strategic communication with senior executives.

The Senior Product Manager will lead data classification capabilities in a Data Security platform, overseeing product strategy and collaborating with various teams to drive accuracy and compliance.

As a Distinguished Engineer at Capital One, you'll drive innovation in cloud banking, lead AI infrastructure, mentor engineers, and define technical strategies for scalable solutions with neural networks.

Lead the transformation of enterprise security through AI, redesigning operations for efficiency, implementing analytics for risk identification, and unifying security systems into an AI-enabled architecture.

The Product Manager for AI Infrastructure will define and manage AI compute products, ensuring hardware and software integration for production platforms, while resolving system integration challenges and driving product decisions.

Lead a team of developers in creating cloud-based solutions using modern technologies, while mentoring peers and collaborating with product managers.

The role involves building AI platforms, designing LLM-powered systems, integrating agents with data sources, and leading technical initiatives.

The Applied Scientist will transform raw data into actionable insights by developing machine learning models for personalization, ranking, and optimization to enhance conversion and revenue. This role emphasizes building production systems, frameworks for experimentation, and communication with team members regarding technical challenges.

Lead the product vision for innovative AI technologies, translating research into marketable products, and collaborating with cross-functional teams.

Develop a risk management strategy, collaborate with stakeholders, lead teams, and ensure compliance while optimizing payment authorization rates.

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

The Solutions Engineer will engage with stakeholders to design AI-powered engineering solutions, bridging business needs and technical execution while guiding customers through AI integration.

Lead and manage Loyalty Engineering teams, drive technical vision, oversee AI-enabled solutions, and cultivate engineering talent to enhance user experiences.

Seeking a Distinguished Technologist to lead AI architecture and design for HPE's Private Cloud AI offerings, focusing on applied AI, agentic AI, and generative AI. Responsibilities include technical leadership, implementation, and mentoring engineers while optimizing AI systems for cloud-based solutions.

Drive yield improvement and process optimization for advanced packaging by building scalable data pipelines, integrating ATE/DFT/fab data, performing statistical and ML-based yield analytics, enabling self-serve analytics, and delivering reports and recommendations across cross-functional teams and external partners.

Develop algorithms for RTL synthesis and digital logic optimization, utilizing machine learning and EDA techniques. Collaborate with design teams to implement solutions.

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