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

Own the technical strategy, architecture, delivery, and engineering team for a core business domain. Build complex production systems spanning areas such as AI, energy trading, retail, real-time generation and demand modeling, data pipelines, and customer-facing applications. Hire and lead engineers, establish team standards, make prioritization decisions in an unstructured environment, collaborate with the CTO and business stakeholders, and remain hands-on with challenging technical problems.

Own full-cycle technical recruiting across software engineering, hardware, AI, trading, and quantitative roles. Develop sourcing strategies, assess candidates, manage pipelines, facilitate debriefs, deliver strong candidate experiences, negotiate offers, and close highly sought-after talent. Partner with hiring managers and department heads to understand hiring needs, timelines, and recruitment priorities. Use ATS tools, reporting, and data-driven recruiting practices.

Own reliability, performance, and scalability of Postgres and ClickHouse databases. Build scalable data pipelines, design analytical schemas and DBT models, migrate data to ClickHouse, implement data quality checks, eliminate duplicates, and manage database infrastructure via IaC.

Design, build, and scale embedded connectivity and security for distributed energy devices. Implement networking (Ethernet/Wi‑Fi/Thread/Zigbee/BLE), secure provisioning, OTA firmware pipelines, telemetry, and diagnostics. Support testing, certification, manufacturing validation, and cross-functional collaboration from prototype to deployment.

Define and build Fuse's inference-serving architecture and stack, including request routing, batching, scheduling, and autoscaling for latency-sensitive workloads. Own model-level optimizations (quantisation, distillation, speculative decoding), translate performance SLAs into capacity plans, and integrate low-level GPU/CUDA performance work with serving infrastructure. Set benchmarks, tooling, and act as technical owner of inference performance and reliability.

Design, implement, and optimize low-level CUDA kernels for transformer inference. Profile and eliminate GPU bottlenecks, apply kernel fusion, optimize memory access and mixed-precision kernels, build caching for autoregressive decoding, benchmark performance, and maintain CUDA libraries and tests.

Develop and optimize CUDA kernels and GPU-accelerated software for latency-sensitive, high-throughput workloads. Profile and tune GPU performance, scale multi-GPU/multi-node systems, build tooling to correlate GPU utilization with real-time energy/grid signals, collaborate with infrastructure and ML teams, and contribute to libraries and best practices for GPU performance in data center environments.

Build and maintain iOS and Android apps, own features end-to-end, implement high-quality UI/UX, ship consumer-facing AI (including on-device ML) to production, integrate REST APIs, troubleshoot production issues, and contribute to mobile architecture.

The Senior/Lead Backend Engineer will develop backend infrastructure for a renewable energy company, including real-time digital twin creation and energy app backend development.