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

Conduct cutting-edge machine learning research involving frontier models, reinforcement learning, post-training, scalable oversight, synthetic data, safety, evaluation, and alignment. Interns develop and improve production ML systems, research new methods, conduct experiments, and may publish or ship work with mentorship from researchers and collaboration across industry and academia.

Design responsive, accessible, high-performing web experiences for Scale's digital properties, primarily scale.com. Create wireframes, prototypes, high-fidelity mockups, reusable design systems, components, and page templates. Partner with engineers and cross-functional stakeholders to communicate design intent, review implementations, evolve the brand, and improve user experiences. Explore emerging AI tools, interaction patterns, analytics, and experimentation to deliver innovative, scalable digital experiences.

Leads Scale’s global systems integrator partnership strategy, ecosystem expansion, and revenue growth. Responsibilities include selecting and managing GSI partners, negotiating alliance agreements, developing co-sell and joint solutions, enabling certified partner practices, generating sourced and influenced pipeline, and overseeing post-signature execution. The role requires strong relationships with major consultancies, enterprise AI or cloud partnership experience, complex commercial negotiation skills, and the ability to influence cross-functional teams without direct authority.

Leads strategic partnerships with frontier AI labs and foundation model providers. Builds joint go-to-market, co-selling, technology, and commercial partnerships; drives partner-sourced revenue, integrations, joint offerings, and enterprise deployments. Coordinates with sales, product, engineering, research, finance, legal, and marketing teams while tracking the AI model landscape and managing post-signature execution, launches, and business reviews.

Design and develop shared platform systems, foundational data platforms, cloud infrastructure, orchestration, and software delivery tooling. Partner with stakeholders and cross-functional teams to define and deliver features, improve engineering practices, and communicate technical concepts. The role requires expertise in backend systems, distributed systems, public cloud, containerization, databases, orchestration, and CI/CD, with opportunities to support AI-focused products.

Lead the architecture, development, and operation of a reliable orchestration platform for distributed workflows. Build workflow primitives, APIs, and infrastructure supporting scheduling, retries, state management, observability, security, scalability, and developer experience. Partner with cross-functional teams, establish engineering standards, and drive technically complex projects from design through production operation.

Design, evaluate, and deploy production frontier AI agents that combine LLMs, retrieval, memory, tool use, and traditional ML. Build retrieval and memory systems, multi-agent coordination, evaluation frameworks, and production engineering (reliability, observability, safety). Partner with enterprise customers to translate problems into scalable AI architectures and run experiments to measure business impact.

Own outbound prospecting, customer education, discovery, and Stage 2 qualification for enterprise AI opportunities. Generate and qualify pipeline, explain AI capabilities and workflows, develop customer narratives, coordinate with Solutions Engineering, Marketing, and GTM Strategy, and transition qualified opportunities to Account Executives. Maintain CRM hygiene and pipeline visibility while building expertise in enterprise AI deployment patterns and customer use cases.

Provide product-focused IP counsel across the product lifecycle for AI/ML systems, advising on IP strategy, data and open-source licensing, patent and trademark management, commercial agreements, risk mitigation, and cross-functional training. Partner closely with Research, Product, Engineering, and business teams to embed IP protection and ensure compliance while supporting patent prosecution and enforcement globally.

Own the enterprise revenue reporting layer, including pipeline dashboards, metric definitions, forecasting, funnel diagnostics, CRM data integrity, and executive business reviews. Analyze conversion, coverage, velocity, and revenue trends to guide capacity, territory, pricing, and growth decisions. Support planning, quota setting, compensation modeling, and GTM system automation while partnering with Finance, Legal, GTM Engineering, and enterprise sales leadership.