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

Lead AfterQuery’s enterprise data acquisition strategy, identify and prioritize target data assets, negotiate high-value purchase and licensing agreements, manage data partners, and ensure legal, IP, governance, and technical requirements are met. Own acquisition budgets, pipelines, forecasting, and ROI reporting while collaborating with Engineering, Operations, Legal, and Research to package data for foundation model training.

Owns final quality reviews for datasets containing code, technical, reasoning, and knowledge-work data. Leads QC processes and tooling, partners with infrastructure engineers to automate workflows, identifies systemic quality issues, provides feedback to contributor training, and reports quality metrics, error rates, root causes, and trends to leadership. The role also supports cross-functional operational initiatives in a fast-moving AI research environment.

Run full-cycle recruiting for business and operations roles, including sourcing, screening, interviewing, candidate closing, and talent pipeline development. Partner with business leaders and the executive team to define hiring profiles, prioritize searches, improve interview rubrics and scorecards, support candidate experience, and track recruiting funnel performance. The role requires recruiting high-caliber candidates from finance, consulting, private equity, technology, and related fields in a fast-paced, five-day in-office San Francisco environment.

Design and build post-training infrastructure for supervised fine-tuning, reinforcement learning, and model evaluation. Develop reproducible pipelines for data preparation, versioning, sampling, training, checkpointing, and experiment tracking. Integrate systems with partner training stacks, model APIs, compute environments, and evaluation platforms. Run controlled experiments to measure dataset impact on model behavior, analyze noisy results, identify confounders, and produce actionable conclusions.

Own planning and execution of technical research programs spanning post-training, enterprise initiatives, fellowships, evaluations, and partner research. Translate ambiguous objectives into milestones, owners, dependencies, success criteria, and decision points. Track experiment progress, risks, blockers, partner dependencies, and releases while aligning researchers, engineers, program leads, and external partners. Apply working knowledge of LLM development, datasets, supervised fine-tuning, reinforcement-learning post-training, and evaluation.

Lead GTM/RevOps execution: own CRM and pipeline hygiene, analytics and forecasting, RFIs, contract-to-cash, sales-stack automation, follow-ups, and customer engagement cadences to scale revenue operations and reduce manual work.

Lead supply-side growth for a talent marketplace: design sourcing strategy, build scalable acquisition channels and automation with engineering, forecast supply, optimize marketplace operations, recruit and manage a growth team, and transform manual playbooks into productized systems that increase contributor quality and retention.

Design datasets, evaluation rubrics, and reward signals for RLHF/RLVR; build real and synthetic data pipelines; run experiments modeling annotator behavior; develop quantitative metrics for dataset quality, diversity, and downstream impact; partner with research teams to translate training objectives into data and evaluation specs.

Partner with the CEO and operations team to run special projects end-to-end, build operational capabilities (billing, revenue ops, BD support), gather and analyze qualitative and quantitative data, support recruiting and administrative finance/office functions, identify and fix operational inefficiencies, and document and hand off durable processes.

Lead and deliver high-impact dataset and data-solution projects for frontier AI customers. Manage client relationships, coordinate specialist engineering and research teams, design dataset specifications, scope and execute projects end-to-end, and support cross-functional operational initiatives to drive revenue and product development.