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

Lead account-based marketing programs for strategic enterprise accounts across healthcare, financial and professional services, and consumer verticals. Own ABM strategy, multichannel campaign execution, account planning, stakeholder engagement, KPI reporting, pipeline attribution, and repeatable playbook development. Partner with enterprise sales, growth marketing, content, product marketing, and field teams while managing creative production and fulfillment partners.

Build and ship software for AI applications supporting government decision-making. Responsibilities include developing guardrails, RAG and agent orchestration systems, data pipelines, evaluation infrastructure, anomaly detection, audit interfaces, and full-stack mission-data tools. Deploy and harden applications in secure, air-gapped, and cloud environments while working directly with government stakeholders.

Lead initiatives to drive revenue and growth in Generative AI, collaborating with teams and developing strategies aligned with market needs.

Lead Scale’s Connectivity engineering team, owning architecture, strategy, and development of API integrations, distributed systems, and data-platform capabilities. Build and ship end-to-end product features, collaborate with internal and external stakeholders, manage the full product lifecycle, and deliver high-quality experiments rapidly. The role also includes mentoring engineers, influencing team culture and processes, and translating business and product ideas into scalable engineering solutions.

Manage and grow a large global contributor community for Scale’s Generative AI business. Develop engagement, retention, communications, feedback, and dispute-resolution strategies; oversee community platforms, virtual events, sentiment monitoring, and contributor messaging. Use metrics and feedback to improve operations and product strategy, coordinate cross-functional stakeholders, remove blockers, and maintain cohesive communications. The role also includes managing at least one direct report and executing operational initiatives directly.

Software Engineering Interns will build and ship production software for AI systems, including data pipelines, evaluation infrastructure, agentic applications, fraud detection, matching algorithms, contributor tools, and AI infrastructure products. Interns own roadmap work with mentorship and collaborate on scalable, high-quality products. The role requires product engineering experience, prior software engineering internship experience, large-scale data systems experience, and familiarity with Python, TypeScript, React, and/or MongoDB.

Build and ship customer-facing software products and AI applications, including data pipelines, evaluation infrastructure, agentic systems, fraud detection, matching algorithms, contributor tools, and RAG applications. Collaborate directly with customers, process large-scale data, integrate APIs and services, and iterate quickly on high-quality products.

Own the technical foundation for building, packaging, executing, verifying, and scaling reinforcement learning environments. Design sandboxed execution, rollout orchestration, trajectory capture, verifier frameworks, environment versioning, and authoring tools. Build high-throughput infrastructure and reliable reward signals, instrument real applications, develop task suites, and defend against reward hacking. Provide staff-level technical leadership across engineering and research teams while shipping complex production systems.

Product Manager for Gen AI Platform to drive strategy, execute product roadmaps, and manage cross-functional teams while ensuring quality training data systems for AI models.

Research and develop novel post-training methods such as SFT, RLHF, reward modeling, and preference optimization for text and multimodal LLMs. Analyze model behavior, improve alignment and generalization, mitigate bias, enhance robustness, and publish findings at leading AI conferences. Collaborate with engineers, researchers, and foundation model labs to establish data-driven AI development practices and provide technical and strategic guidance.