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

Support the design, integration, characterization, testing, and validation of autonomous hardware systems for construction equipment. Evaluate components, write Python, C++, C, or Rust scripts for sensor data analysis and test automation, run tests, collect data, and document results. The intern will work with embedded compute platforms, autonomous sensors, communication protocols, and hardware integration under senior engineer guidance.

Sensor Systems Engineering Intern responsible for selecting and placing sensors on autonomous heavy construction equipment. Analyzes sensor coverage, occlusion, blind spots, field of view, range, and mounting constraints; develops geometry and coverage tools; conducts performance, cost, durability, and integration trade studies; prototypes mounting concepts; validates configurations on real machines; and translates findings into hardware requirements while collaborating with perception, hardware, and safety teams.

Integrate and optimize LLM and VLA models within Bedrock’s Rust-based onboard infrastructure for autonomous heavy machinery. Responsibilities include profiling inference performance, optimizing models with TensorRT and edge runtimes, streaming camera and LiDAR data, eliminating memory, compute, and IPC bottlenecks, and validating improvements on autonomous equipment. The role requires systems programming, GPU and CUDA knowledge, real-time systems expertise, and experience with PyTorch or JAX.

Train and evaluate world models using real autonomous construction-machine fleet data. Explore model architectures, conduct ablations, build evaluation metrics and harnesses, and collaborate with behavior and controls teams to connect model outputs to planning and control on excavators. Present findings and establish reliable foundations for future development.

Test and validate camera, lidar, and supporting sensor hardware for autonomous excavators. Responsibilities include building test fixtures, integrating wiring and DAQ systems, running lab and field test campaigns, automating data collection with Python, processing sensor logs, debugging electrical and mechanical hardware, selecting test equipment, documenting results, and presenting conclusions that guide sensor and system design.

Define and maintain system-level architecture and safety requirements for autonomous construction equipment. Lead functional safety concepts, HARA, FMEA, STPA, and FTA analyses; establish safety mechanisms, verification and validation plans, and requirements traceability. Collaborate across hardware, software, and mechanical teams, support design reviews and root cause analysis, and make technical tradeoffs affecting system performance and safety.

Lead full-cycle recruiting for AI/ML, perception, robotics, and technical leadership roles. Partner with engineering leaders and founders on hiring strategy, source specialized talent through research and technical networks, negotiate competitive offers, and manage candidate closing. Build AI-powered recruiting tools, maintain pipeline data, represent the company at conferences, strengthen employer branding, scale recruiting operations, and mentor future recruiters.

Lead data science across autonomy, safety, and product by analyzing machine telemetry and operational data, defining metrics, designing experiments, and partnering with ML platform and engineering to deliver insights that improve system performance and safety.

Lead and scale all accounting operations (GL, revenue recognition, AP/AR, payroll, consolidations, equity), drive month-end close, oversee fintech revenue streams, build internal controls and systems, partner with FP&A and product/engineering to automate financial workflows, support audits, SOX readiness, and board/investor reporting.

Design and implement onboard control algorithms and system models for heavy construction robots, develop MPC and RL-based controllers, perform system identification and simulation of multi-DOF arms and vehicle dynamics, and ensure safety-critical real-time embedded performance.