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

Lead finance for accelerator compute investments: build detailed bottoms-up financial models, budgeting, forecasting, variance analysis, and capacity planning. Translate technical compute dynamics into financial frameworks, identify optimization opportunities across cloud and chip economics, and partner with engineering and research to inform investment decisions and implement scalable financial planning tools.

Design, build, and operate distributed systems supporting reinforcement learning at frontier scale. Responsibilities include scheduling, data movement, storage, networking, fault tolerance, autoscaling, observability, automation, and performance optimization across large accelerator fleets. The role requires debugging complex distributed failures, preserving training correctness, collaborating with researchers, and creating resilient systems that continue operating through hardware failures and changing workloads.

Develops reinforcement learning algorithms, model architectures, and experimental infrastructure for frontier-scale training. Responsibilities include scaling RL across model size, context length, and compute; diagnosing numerical, algorithmic, and systemic failures; optimizing performance and cost; and managing end-to-end large-scale runs. The role requires rigorous experimentation, distributed training expertise, quantitative modeling, and strong programming across the ML systems stack.

This role involves delivering analytics for Finance & Strategy, developing data pipelines, and producing insights to inform leadership decisions.

Owns the design and operation of a core go-to-market funnel domain in Salesforce, including lifecycle stages, process rules, data models, routing, ownership, forecasting, automation, and integrations. Partners with GTM leadership, RevOps, and developers to translate business needs into system solutions. Builds declarative Salesforce configurations, writes technical specifications, and leads discovery, testing, enablement, and adoption measurement across customer lifecycle processes.

Build and deploy AI systems for life sciences research institutions. Partner with scientific and engineering teams to integrate Claude into research workflows, develop MCP servers, benchmarks, agent skills, and domain-specific infrastructure, and identify deployment challenges involving heterogeneous data and auditability. Create documentation and technical content that enables partners to self-serve and scale successful solutions across the life sciences ecosystem.

Build and operate secure, reliable cloud infrastructure, storage systems, and data pipelines for specialized legal and privacy workloads. Translate legal, privacy, and security requirements into scalable, auditable architectures; manage chain of custody and data integrity; partner with Legal, Privacy, Security, Research, and Infrastructure teams; and deliver production systems under fixed deadlines. The role also requires advising nontechnical stakeholders and extending shared infrastructure for novel legal requests.

Design and ship polished product experiences for Anthropic’s Claude Developer Platform. Collaborate with product managers, engineers, and AI researchers to define product vision, workflows, primitives, and roadmaps. Create high-quality interfaces, prototypes, and designs for complex developer tools and AI capabilities while understanding technical architecture. Work quickly in an ambiguous startup environment, using code and AI tools to prototype, iterate, and improve user trust, consistency, and overall product quality.

Build and operate cloud inference launch infrastructure for Claude across AWS, GCP, Azure, and future providers. Develop validation pipelines, CI/CD systems, performance benchmarks, shadow traffic testing, correctness checks, and observability. Integrate new model architectures and inference features, resolve cross-cloud reliability and performance issues, optimize accelerator usage, and reduce deployment cycle times. Collaborate with inference teams and cloud partners while owning large-scale distributed systems and automation end to end.

Own full-cycle recruiting for Anthropic’s Communications team, from intake through offer. Partner with senior leaders, source passive communications talent, advise on talent markets and compensation, manage high-touch candidate processes, and turn hiring data into recommendations. The role may also support Brand and Marketing hiring, executive searches, and confidential recruiting. Success requires strong communications recruiting expertise, discretion, data-informed judgment, and the ability to operate effectively in a fast-paced AI company.