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

Own the full B2B sales cycle for small and mid-sized business accounts, including outbound prospecting, inbound qualification, discovery, negotiation, and closing. Build pipeline, manage target accounts, assess deal risk, communicate financial value, and develop customer relationships that drive renewals and expansion. The role requires startup experience and a proven ability to close deals worth at least $80,000 in annual contract value.

Develops and optimizes low-level compute software for machine learning accelerator chips. Responsibilities include tuning training and serving pipelines, benchmarking speed and memory use, profiling hardware performance, advising model researchers on runtime impacts, and creating compute routines for language-model workloads. The role requires strong operating systems, CPU/GPU architecture, machine learning, C/C++, performance engineering, and hardware-software co-design expertise, with staff-level ownership of chip or compiler software.

Own end-to-end product interface design for a fast-moving team, including user workflows, prototyping, testing, visual standards, and engineer handoff. Use session recordings, funnel data, and user behavior to guide decisions. Collaborate directly with full-stack engineers on rapid releases while maintaining a distinctive visual and emotional product quality. The role requires strong independent ownership, portfolio-quality UI/UX work, AI-assisted design comfort, and full-time on-site availability in San Francisco.

Work directly with client teams to understand operational processes, translate ambiguous business challenges into automated workflows, and build production-ready software using Python, SQL, APIs, and large language models. Responsibilities include prototyping, requirements discovery, prompt design, autonomous components, evaluation, user enablement, executive communication, and monitoring measurable outcomes after launch.

Build scalable data pipelines that transform raw technical and business materials into structured training tasks and evaluations for machine learning systems. Collaborate with researchers and subject-matter experts to define requirements, review samples, develop quality checks, identify flawed or gameable tasks, and investigate delivery issues to improve future datasets.

Win large enterprise software contracts by building target-account pipelines, sourcing opportunities, leading complex multi-stakeholder sales cycles, developing customer-specific financial cases, navigating approvals and contracts, and closing net-new deals. Partner with leadership on pricing and deal strategy while documenting a repeatable sales playbook. Success requires proven enterprise sales performance, self-sourced pipeline generation, large-contract closing experience, and the ability to engage senior executives and technical stakeholders.

Create short-form video from concept through final edit for major social platforms. Grow the company’s social presence, analyze engagement data, design and execute marketing experiments across social, live, and online channels, and develop operating guides. Contribute to go-to-market strategy, national launch planning, and growth initiatives by translating user, founder, and engineering insights into content ideas.

Works directly with clients to map business processes, define automation requirements, build and test reliable software workflows, deploy solutions into production, monitor performance, and resolve failures. Partners with platform engineers to create reusable capabilities and supports expansion opportunities and business development. Requires strong programming, software validation, customer communication, and independent meeting skills, with experience in forward-deployed engineering or similar technical client-facing roles.

Designs and operates shared infrastructure supporting engineering and review workflows. Builds distributed services, data pipelines, internal tools, and reliable long-running jobs involving external APIs and remote environments. Investigates incidents, improves performance and resource efficiency, strengthens failure recovery, and establishes engineering standards. The role requires production software experience, large-scale systems familiarity, end-to-end project ownership, sound engineering judgment, and strong initiative. Experience with AI task automation, model serving, or model quality testing is advantageous.

Own and improve production AI dialogue systems, create a new automated assistant, establish evaluation, monitoring, and tracing practices, diagnose system failures, stay current with AI developments, and collaborate closely with operations and engineering teams.