Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

As a Customer Success Associate, you will manage client inquiries, identify pain points, and provide solutions while collaborating with various internal teams. You'll need strong communication skills and an understanding of sports betting.

As a DevOps Engineer, you will develop, maintain, and implement Kubernetes clusters for machine learning workloads, collaborate with Data Science and Engineering teams on workload optimization, ensure best practices for software deployment, and respond to system incidents.

The Legal Counsel will negotiate and draft commercial agreements for sports data acquisition, oddsmaking services, and licensing. They will ensure compliance with sports betting licensing, assist with strategic legal policies, manage external legal advisors, and provide general legal services to the leadership team.

The Tennis Data Scientist will develop and improve machine learning and statistical models for sports betting products, contribute to model development and deployment stages, analyze model performance, and adhere to software engineering practices while collaborating with various teams.

As a Frontend Engineer at Swish, you will design and develop a cutting-edge data analytics platform while standardizing development processes. You'll work closely with stakeholders to meet technical requirements, coordinate cross-departmentally, and implement backend solutions using RESTful APIs. An emphasis is placed on producing high-quality, testable software and optimizing data analytics using SQL.

The Staff Software Engineer will lead the development of core backend applications and products, ensuring technical excellence through code reviews, optimizations, and adherence to best practices. They will collaborate in architectural discussions, design and enhance services, and work with data processing technologies to support a variety of business essential products.

Looking for a Research & Experimentation Scientist to enhance sports betting algorithms and models using large-scale data processing techniques. Must have strong leadership skills and experience in machine learning, statistics, and AWS environments.