Perception Software or Machine Learning Engineer

The Role

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 autolabels (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: Experience taking deep learning models from research to real-world production using PyTorch.
• 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

Our roles are often flexible. If you don't fit all the criteria, or are in another location (especially one where we have an office like SF of NY) please apply anyway! We'd love to consider you. 

Join the team bringing advanced autonomy to the built world

At Bedrock, we've assembled one of the most experienced autonomous technology teams in the industry, with deep expertise scaling breakthroughs across transportation, infrastructure, and enterprise software. Our leaders helped put the first self-driving cars on public roads at Waymo, scaled systems for Segment's $3.2B acquisition, and grew Uber Freight to $5B in revenue.

While others debate the future of AI, we're deploying it in the real world. Our systems are already installed on heavy machines across the country, learning on real construction sites and working to reshape the earth with survey-grade precision and exceptional safety. This isn't a simulation—it's autonomous intelligence working on billion-dollar infrastructure projects.

In just over a year, we've raised $80M, put our equipment into the field, and established partnerships with forward-thinking contractors who are integrating our technology into their operations. We're working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage.

Here, algorithms meet steel-toed boots. You'll collaborate with both construction veterans and experienced engineers, tackling problems where your work directly impacts how the physical world get built. If you're interested in applying cutting-edge technology to solve meaningful problems alongside a talented team—we'd love to have you join us.