Machine Learning Engineer: Perception

Reposted 24 Days Ago
San Francisco, CA, USA
Hybrid
Mid level
Robotics
The Role
As a Machine Learning Engineer, you will design and train perception models for robotics, focusing on 3D perception systems. You will tackle complex physical challenges, optimize models for embedded hardware, and collaborate with cross-functional teams.
Summary Generated by Built In
Join the team bringing advanced autonomy to the built world

At Bedrock, we're moving AI out of the lab and into the real world. Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we're deploying autonomous systems on heavy construction equipment across the country, improving safety on job sites and accelerating schedules on critical infrastructure projects.
We're not here debating the future of AI. We're deploying it in the real world. In just two years, we've raised $350M and achieved the first fully autonomous excavator deployments in construction.
This is where algorithms meet steel-toed boots. You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to do meaningful work on hard problems, we'd love to have you join us.

Machine Learning Engineer: Perception

 

Bedrock is bringing autonomy to the construction industry! We’re a group of veterans from the autonomous vehicle industry who are passionate about bringing the benefits of automation to areas in the construction industry currently underserved by the market.

We are looking for engineers with expertise in shipping production 3D perception systems at scale. Successful candidates have architected systems, trained models from scratch, understand the full stack (clustering, detection, classification, and tracking), and have shipped at scale. We use both computer vision and LIDAR-based approaches, so knowledge of either or both is key. Models are just part of the system: you understand data and have good intuition about why models fail. You know how to evaluate corner cases, manage or build data pipelines, use auto-labels (or not), and have a strong understanding of statistical properties of these systems.

 

What You’ll Do:

  • Design Early Fusion Architectures: Develop and train state-of-the-art models (e.g., BEV-based transformers) that fuse raw Lidar and Camera data to solve for object detection and semantic segmentation.

  • Tackle "Messy" Physics: Build perception systems robust enough to handle dynamic occlusion (seeing the robot’s own arm/bucket), particulates (dust, snow, rain), and high-vibration conditions.

  • Deploy to the Edge: Optimize models for inference on embedded hardware. You will debug system-level issues, such as sensor calibration drift and latency bottlenecks.

  • Collaborating with other teams to create state-of-the-art representations for downstream use cases.

What we're looking for:

  • Production ML Experience: 5+ years of experience taking deep learning models from research to real-world production using PyTorch, Tensorflow, or JAX.

  • 3D Geometry & Calibration: You have a deep understanding of SE(3) transformations, homogeneous coordinates, and intrinsic/extrinsic sensor calibration. You understand the math required to project a 3D Lidar point onto a 2D image pixel accurately.

  • Early Fusion Expertise: Practical experience with architectures that fuse modalities at the feature level (e.g., BEVFusion, TransFuser, PointPainting) rather than just fusing final bounding boxes.

  • SOTA Object Detection experience with modern transformer-based architectures (DETR, PETR, etc…) including similar temporal models (PETRv2, StreamPETR, …)

  • Systems Fluency: You are an expert in Python, but you are also comfortable reading and writing systems code in C++ or Rust. You understand memory management and real-time constraints.

  • Data Intuition: You understand that in robotics, better data alignment often beats a bigger model. You are willing to dig into the data infrastructure to ensure ground truth quality.

Ways to stand out:

  • Bonus: Voxel/Occupancy Experience: Experience working with occupancy grids, NeRFs, or voxel-based representations for terrain mapping.

  • Bonus: Top-Tier Research: Published work in conferences such as ICRA, IROS, CVPR, ECCV, ICCV, CoRL, or RSS

Bedrock Robotics is an Equal Opportunity Employer

We’re committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, veteran status, genetic information, or any other protected characteristic.

Reasonable Accommodations

We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process, please let your recruiter know so we can support you.

Skills Required

  • 3+ years of experience in Production Machine Learning
  • Deep understanding of SE(3) transformations and intrinsic/extrinsic sensor calibration
  • Practical experience with early fusion architectures
  • Experience with state-of-the-art object detection using transformer architectures
  • Expertise in Python; comfortable with systems coding in C++ or Rust
  • Strong intuition about data in robotics
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The Company
HQ: San Francisco, CA
56 Employees
Year Founded: 2024

What We Do

Bedrock Robotics brings advanced autonomy to the built world, helping the construction industry build at the pace today's society demands. Our technology upgrades existing heavy equipment, enabling truly autonomous operation with expert level quality and superhuman safety. At a time when we need to build faster than ever—from housing to data centers to factories and energy infrastructure—autonomous construction isn't just an innovation, it's an economic necessity.

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