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

Conduct research on evaluating frontier large language models and AI agents. Analyze model behavior, diagnose capability, reasoning, robustness, and alignment failures, and develop benchmarks for text and multimodal systems. Apply post-training techniques such as supervised fine-tuning, RLHF, and reward modeling to connect failures with training interventions. Collaborate with AI labs, define evaluation best practices, translate findings into technical strategy, and publish research at major conferences.

Build and own technical enablement for customer-facing engineers, including role-based onboarding, ramp criteria, knowledge-base governance, ongoing technical development, and readiness programs. Partner with engineering, enablement, product, sales, and delivery stakeholders; manage concurrent programs, track milestones, maintain documentation health, identify readiness gaps, and report program outcomes to leadership.

The Finance Systems & Automations Manager designs and implements integrations and automations across Finance, Accounting, People, and Recruiting, improving operational efficiency through AI-driven workflows.

Lead cross-functional initiatives to drive multimillion-dollar revenue: partner with product and engineering, own data-labeling operations for strategic projects, provide executive updates, and solve high-impact operational and product problems.

Own Scale’s end-to-end commercial acquisition of proprietary training data for AI environments. Identify high-value data domains and organizations, develop partnership and pricing structures with Legal, conduct outreach, negotiate and close transactions, and translate dataset requirements between commercial and Research teams. Build the acquisition function from the ground up, converting initial hands-on learnings into a repeatable pipeline.

The Research Scientist will design methods and experiments for AI control and monitoring, focusing on safety and robustness in advanced AI systems. Key tasks include developing monitoring techniques, researching layered control mechanisms, and collaborating with policymakers and industry experts.

Lead development of generative AI platforms for U.S. government, ensuring ethical deployment and compliance, managing the full product lifecycle, and engaging stakeholders.

Design and scale multi-cloud infrastructure for an enterprise Generative AI platform. Build integrations with customer cloud/data environments, collaborate with product and customers, deliver experiments to production, and maintain platform reliability and performance.

Owns enterprise deal pricing execution, including financial modeling, ROI analysis, staffing inputs, pricing frameworks, and margin reporting. Builds dashboards, coordinates deal reviews across Sales, Finance, Accounting, Legal, and EPD, and tracks approvals and cycle times. Identifies process improvements, supports forecasting and P&L analysis, and contributes to pricing strategy, proposals, and value engineering initiatives.

Lead and grow a research team focused on generative AI, LLMs, post-training, evaluation, and agent/RL environments. Define multi-year research roadmaps, drive execution from prototype to deployment, collaborate cross-functionally, publish and present externally, and cultivate an inclusive, high-performing team culture.