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Hadrian

Robotics Software Engineer, Perception

San Francisco Bay Area, CAOnsite · United States
FullTime · Engineering, Product, Design
POSTED 10 AUGVERIFIED 14H AGO
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Pay · posted
$299k–359k
mkt median $200k
Open for
86d
since 10 Aug
Hiring · 30d
160
0 net · open roles

Hadrian - Manufacturing the Future

Hadrian is building autonomous factories to reindustrialize America. By combining AI, advanced software, robotics, and full-stack manufacturing, we help aerospace and defense companies build rockets, satellites, aircraft, ships, and other mission-critical systems up to 10x faster and at significantly lower cost.

Following our $1.37B Series D at a $7.87B valuation, Hadrian is rapidly expanding our manufacturing footprint, launching new capabilities across welding, casting, forging, electronics, additive manufacturing, and more, while scaling our Factory-as-a-Service platform to transform how critical products are built.

Backed by leading investors including JPMorgan Chase, Valor Equity Partners, Andreessen Horowitz, Founders Fund, 137 Ventures, Lux Capital, T. Rowe Price, and Morgan Stanley, we’re building the future of American manufacturing—and looking for exceptional people to help make it happen.

If you’re ready to take on the most challenging and rewarding work of your career while helping create American manufacturing jobs for generations to come, you’re exactly who we’re looking for.

The Role

The Autonomous Factory Systems team builds the software that gives Hadrian's factories the ability to sense, decide, and act autonomously. This includes the core robotics stack — perception, behaviors, planning, collision avoidance, and high-level control — alongside orchestration between robots and manufacturing machines and the hardware abstraction layer that connects our software to the machines on the floor.

Perception is central to the future of autonomous systems in the factory. In this role will lead the technical direction of the Autonomous Factory Systems organization’s Perception team. You will be defining the technical roadmap, shaping the architecture, and driving the work that will meaningfully expand what our robots can sense, understand, and act on. This is a deeply hands-on role for someone who brings sharp technical depth and the experience to drive alignment across teams working at the cutting edge of industrial robotics.

What You’ll Do

Define and drive the multi-year technical roadmap for the Perception Team; align perception capabilities with the broader Autonomous Factory Systems strategy and surface upstream dependencies and risks early

Lead architecture of the full perception pipeline. Object detection and tracking, semantic and instance segmentation, 6-DoF pose estimation, and scene understanding, designed for the reliability and throughput demands of industrial environments

Define the integration surface between perception and adjacent systems (motion planning, manipulation, control, simulation); establish clear, well documented contracts that downstream teams can build against with confidence

Drive sensor fusion strategy across LiDAR, structured light, RGB, and depth cameras; collaborate with hardware teams on sensor selection and calibration pipelines

Establish rigorous practices for the team: data collection and labeling pipelines, model training and evaluation workflows, deployment practices, and validation criteria across simulation and real-world environments

Represent perception in cross-functional design reviews and planning; engage with hardware vendors and research collaborators where relevant

Continuously evaluate state-of-the-art research; make deliberate, justified decisions about when and how to incorporate advances into production systems

What We’re Looking For

10+ years of software engineering in computer vision, robotics perception, or autonomous systems, with a track record of technical leadership at Staff or Principal level (or equivalent scope)

Expert level command of 3D computer vision: point cloud processing, depth estimation, stereo and structured light systems, multi-view geometry, and/or LiDAR-based algorithms in production

Strong machine learning foundations: model architecture, training infrastructure, and production deployment, with the judgment to know when and how to apply learned approaches versus classical methods

Source · HadrianFirst seen 2 NovOriginal ↗