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

Integrate security into software delivery and infrastructure workflows across AWS and GCP. Build scanning into CI/CD pipelines, maintain security guardrails, secure containerized workloads, implement least-privilege access and secrets management, and support compliance with SC TRM and BNM RMiT. Improve monitoring, vulnerability reporting, incident readiness, and secure delivery practices while collaborating with platform and engineering teams using multiple programming languages.

Lead production-grade ML systems: build data pipelines, training and evaluation workflows, and scalable GPU inference. Fine-tune and adapt large models (LoRA, QLoRA, SFT, DPO, distillation), optimize deployments for latency/cost/reliability, and collaborate with product and engineering to ship robust, observable model-driven features.

Leads the end-to-end execution layer for machine learning, including data pipelines, large-model training and fine-tuning, evaluation, inference, deployment, monitoring, and reliability. Designs scalable GPU-based systems, optimizes performance and cost, partners with research and application engineering, and translates model capabilities into measurable production improvements. Also provides technical leadership, judgment, and support for high-impact ML delivery.

Lead the end-to-end ML execution: build and operate data pipelines, training and evaluation systems, and scalable inference. Fine-tune and optimize large models (LoRA/QLoRA/SFT/DPO/distillation), ensure GPU efficiency, monitor production quality, collaborate with product and application engineering, and rapidly ship reliable, safe ML solutions that translate research into production.

Design, build, and operate large-scale ML systems across data, training, evaluation, inference, and deployment. Lead GPU-optimized training and inference pipelines, ensure reliability, performance, safety, and seamless integration into products. Own production deployments, monitoring, and cross-functional best practices to drive measurable model improvements and efficient research-to-production cycles.

Lead high-priority, cross-functional initiatives spanning product, engineering, operations, hiring, and business development. Partner with leadership to solve business and product challenges, research markets and opportunities, build teams and processes, and improve operational execution. The role requires strong ownership, business judgment, communication, adaptability, and the ability to deliver outcomes in a fast-moving environment.

Build and own an AI-native digital banking business, defining its proposition, roadmap, business model, and customer experiences. Lead accounts, cards, payments, savings, financial automation, and servicing initiatives while owning P&L, deposits, revenue, unit economics, and costs. Build the team and operational capabilities, collaborate with product, engineering, and AI teams, and manage banking partnerships, regulatory readiness, and market expansion.

Work directly with the CEO to convert priorities into executed plans across product, hiring, licensing, partnerships and market launches. Track OKRs, decisions, blockers, owners and deadlines; prepare briefs, research notes and follow-ups; identify and close execution gaps; own urgent cross-functional problems and coordinate product, engineering, finance, legal, compliance, operations and country teams.

Drive high-priority cross-functional initiatives, partner with leadership to solve product and business challenges, build teams/processes, research markets and opportunities, and deliver operational improvements and measurable business outcomes in a fast-moving environment.

Work directly with leadership to drive high-priority, cross-functional initiatives across product, engineering, hiring, operations, and BD. Lead projects end-to-end, research markets, build teams/processes, and deliver measurable business outcomes in a fast-moving startup environment.