Bedrock Robotics

Hardware Engineer

• Support the design, characterization, integration, and validation of Bedrock autonomy hardware and related systems under senior-engineer guidance
• Assist with component evaluations for autonomous hardware platforms
• Write sensor-data analysis and test-automation scripts in Python, C++, C, or Rust
• Run tests, collect data, and clearly document results for the engineering team
• Work alongside senior engineers to help deliver robust autonomous hardware systems to the field
• Contribute to hardware supporting autonomous systems on heavy construction equipment

Hardware Engineer Intern

SDET

• Develop and execute black-box test plans characterizing actuator behavior on machines and test stands
• Instrument hardware, set up data acquisition, and collect clean, trustworthy datasets
• Characterize response behavior including latency, deadband, hysteresis, and saturation across temperature, load, and wear conditions
• Compare real machine data against simulation output and quantify divergences
• Provide findings to controls and simulation teams as concrete model improvements
• Automate test execution and reporting
• Work on autonomous systems for heavy construction equipment, improving job-site safety and accelerating infrastructure project schedules

Validation & Verification Test Engineer, Internship

Infrastructure Engineer

• Integrate open-source and proprietary LLM/VLA models into Bedrock’s onboard Rust middleware stack alongside perception, planning, and control pipelines
• Profile and optimize model execution using TensorRT, vLLM, ExecuTorch, or custom edge inference runtimes for NVIDIA Jetson Thor
• Streamline camera and LiDAR sensor tokenization to feed real-time streams directly to models without latency spikes in vehicle control loops
• Identify and eliminate bottlenecks across memory bandwidth, compute, and IPC using Nsight Systems, Nsight Compute, and eBPF
• Validate performance optimizations directly on heavy autonomous machinery at Bedrock test sites
• Work on autonomous systems for heavy construction equipment, improving job-site safety and accelerating critical infrastructure schedules

Internship – Onboard Infrastructure Engineer, ML Inference

Systems Engineer

• Analyze sensor coverage, occlusion, and blind spots for candidate sensor suites on new machine types
• Build or extend tooling modeling field of view, range, and coverage geometry
• Run trade studies balancing performance, cost, durability, and mounting constraints
• Prototype mounting concepts and validate coverage assumptions on actual machines
• Convert analysis into sensor requirements and specifications for hardware implementation
• Collaborate across perception, hardware, and safety teams
• Work across sensor physics, autonomy systems architecture, mechanical integration, and design

Internship – Sensor Systems Engineer

Machine Learning Engineer

• Train and evaluate world models on real fleet data collected from autonomous machines in the field
• Run architecture explorations and ablations, and make a defensible case for what is working
• Build evaluation harnesses and metrics to assess model improvements
• Partner with behavior and controls teams to connect model outputs to planning and control
• Present findings and provide a foundation for the team to build upon
• Work on autonomous systems for heavy construction equipment, improving job-site safety and accelerating critical infrastructure schedules

Internship – Behavior Machine Learning Engineer, World Models

QA Engineer

• Own the camera pipeline end to end: diagnose image quality failures, tune ISP parameters, and validate improvements across the full operating radiometric range from bright daylight to night with machine-mounted illumination
• Own embedded camera driver development and integration: register-level control, frame synchronization, and software interfaces that expose runtime ISP parameter control to the autonomy stack
• Characterize existing ISP pipeline behavior from first principles: identify root causes of image quality failures using parameter-level access, histogram analysis, raw vs processed frame comparison, and controlled test scenes
• Tune ISP and imager settings (exposure, white balance, HDR sub-frame ratios, tone mapping, noise reduction) to optimize image quality for both ML perception models and remote assistance/teleoperation
• Establish and run test protocols that confirm ISP changes improve low-light performance without adversely affecting existing daytime model performance or training data compatibility
• Work closely with perception, autonomy, and sensing engineering to translate scene and platform constraints (yaw rates, lux levels, detection ranges) into concrete ISP tuning targets
• Debug camera issues from sensor/ISP register state through to captured imagery, both in the lab and in the field
• Define and drive image quality characterization methodologies (SFR/MTF, noise, dynamic range, photon transfer curves) and track performance across hardware and ISP firmware generations
• Manage relationships with ISP, camera module, and embedded compute vendors

Senior Camera Pipeline, Image Quality Engineer

Analytics Engineer

• Develop perception algorithms for re-id of vehicles on massive construction sites
• Extend, modify and adapt existing perception signals for analytics needs
• Work with customers to define and scope what is possible with advanced perception systems on-site
• Deploy models and analytics directly to fleets of machines

Machine Learning Engineer – Perception Analytics

• Partner with teams like Finance, Marketing, Field Operations, and PeopleOps as their technology consultant, turning business needs into concrete, well-documented plans the broader infrastructure team can execute against
• Own the layer of shared services that business systems are built on top of. New tools come in and you make them fit the environment cleanly rather than bolt on beside it. You see each rollout through to go-live.
• Build with the tools already in place: modify HCL to deploy a new service, wire up integrations in platforms like Zapier or Rippling's workflow engine, or write a small Python Lambda when the job calls for it
• Own the workplace technology standards for new sites, from internet connectivity to video conferencing, and deploy them across office expansions in San Francisco, New York, Austin, and Phoenix
• Coordinate the vendors and services behind each site buildout, staying accountable from first conversation to final handoff
• Co-author the Requests For Discussion (RFDs) behind major system rollouts, often guiding a business partner through their first, so Bedrock ends up with systems that fit the company rather than a stack that fragments with every new tool
• Pull in the right specialists, from the Identity lead for SSO to the wider infrastructure team for everything downstream, while remaining the accountable owner end to end
• Drive the evolution of the standards you own so every deployment lands better than the last

IT Systems Engineer

Operations

• Manage a distributed team of Fleet Technicians across multiple states
• Build technician schedules and ensure regional fleet commitments are met
• Handle regional fleet performance metrics and report regularly
• Conduct root cause analysis on field issues and manage parts inventory
• Ensure compliance with regulations governing field service operations
• Serve as the primary contact for customer relationships in the Central Region