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

The Sales Assistant supports the Sales Team by managing advertising orders, collaborating with Account Executives, and ensuring accurate invoicing and communication with clients.

Drive sales of atomic spectroscopy instruments (AA, MP-AES, ICP-OES, ICP-MS), supplies and service across an assigned Pacific Northwest territory. Build customer relationships, identify solutions, develop sales approaches to meet quota, lead cross-functional projects, and travel up to 50%.

Develops and maintains ArcFM applications using ESRI technologies, focusing on GIS implementation for Electric and Gas utility sectors.

The VP of Corporate Communications and Investor Relations will lead strategic communications to enhance the company's identity and reputation, collaborating with various stakeholders to effectively communicate the corporate message.

The Senior Product Architect designs and builds internal tools for improved team efficiency, balancing architecture and hands-on coding, focusing on customer experience and internal operations.

The Regulatory Reporting AVP will coordinate the management of regulatory reporting incidents and support compliance with regulatory standards across various teams.

Lead and develop a team of Project Accountants to ensure accurate project financials including revenue recognition, billing, forecasting, collections, WIP and month-end close. Oversee audits, contract reviews, ERP implementation, training, standards, and liaison with IT. Support 20-30 projects, manage reporting to finance leadership, and provide year-end audit support. Travel ~10-15%.

Provide legal counsel to SB Energy's teams on energy infrastructure projects, managing outside counsel and reviewing contracts for financing and acquisitions.

As a Senior Software Engineer, you'll develop end-to-end systems, ensuring scalability and quality, collaborating closely with executives to align technical solutions with business goals.

The Senior ML Data Scientist will develop machine learning models to detect fraud, manage the data science lifecycle, and collaborate with teams on strategies.