Machine Learning Jobs in Oakland, CA

The Senior Data Scientist will analyze data to improve business outcomes, build data models, leverage machine learning, and support product teams with strategic insights.

The Engineering Manager - Machine Learning will lead a team developing ML models for growth personalization and financial insights, driving measurable impact across Plaid's products.

The Marketing Associate supports marketing campaigns, analyzes impact, prepares reports, and collaborates with teams while maintaining attention to detail.

Responsible for generating new business opportunities, managing sales processes, building client relations, and exceeding sales quotas in a competitive environment.

The Client Solutions Associate will manage client relationships, oversee project delivery, and collaborate with teams to deliver innovative solutions. Strong consulting and technical background required.

The Senior Account Executive will develop relationships, generate new business opportunities, analyze markets, and manage the sales process to drive growth in Sports, Media, and Marketing sectors.

Consultants will design, build, and implement AI strategies and systems, guiding clients in adoption and maximizing AI value.

This role involves advancing the Streaming Monetization product, collaborating with sales teams, conducting market research, managing revenue analytics, and ensuring effective sales enablement and business operations.

Lead software engineer in Generative AI, developing infrastructure for AI applications, collaborating across teams, and mentoring junior members.

The AI Solution Manager role involves leading AI solution deployment, customer engagement, and cross-functional teams to develop and deliver tailored AI applications for Fortune 500 clients.

As an Applied Scientist III, you will shape AI strategies, develop scalable applications using cutting-edge technologies, and mentor junior scientists at Capital Group.

The Software Engineer will build and scale platform components, collaborate with product teams, and set technical direction in a fast-paced AI role.

The Principal Data Engineer will provide architectural solutions, lead data engineering initiatives, and oversee large complex projects while mentoring and collaborating with other team members.

Join Equilibrium Energy as a Staff/Sr Staff Software Engineer to enhance the Science Platform for ML model deployment, requiring strong Python and ML expertise.

Lead and mentor the data science team, define research roadmaps, prototype NLP architectures, and engage with industry audiences.

As a Staff Software Engineer, you'll architect and build the ML platform infrastructure, guiding AI initiatives and mentoring engineers while enhancing the AI/ML stack for scalable performance.

As a Senior Technical Sourcer at Abridge, you will identify and engage exceptional senior technical talent in Engineering and Product roles, develop market insights, and build long-term relationships with candidates.

The Machine Learning Engineer will train and deploy ML models for parsing unstructured data, improve LLM accuracy, and build data pipelines.

As an AI/Machine Learning Engineer, you will design and implement machine learning solutions for healthcare applications, develop ML pipelines, and collaborate with clinical experts to enhance patient care using AI.

In this role, you will build sales pipelines through outreach, generate qualified leads, and support sales efforts while working closely with Marketing and Sales teams.

Join Nextdoor's machine learning team to build data-intensive products, develop ML models, analyze datasets, and enhance user experiences. Collaborate closely with product and data science teams.

The Machine Learning Engineer will build data-intensive products, deploy ML models, analyze datasets, and collaborate with product teams to enhance Nextdoor's platform.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

The Staff Data Scientist will enhance engagement strategies using machine learning, lead cross-functional projects, mentor junior scientists, and collaborate on product insights.

Design and develop innovative deep learning methods for biomolecular design, collaborating with biology teams, prototyping new algorithms, and presenting results.