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Machine Learning Engineer – Robotics
We’re looking for a highly motivated engineer with experience deploying machine learning algorithms to physical systems in the real world.
The ideal candidate has hands-on experience in perception (e.g., object detection, semantic segmentation, depth estimation) and/or behavior learning methods (e.g., Vision-Language-Action (VLA) models, diffusion policies). More importantly, you’ve shipped ML models to robots in production environments, and you understand the complexities that come with it.
What you’ll do:
Develop and optimize real-time ML models for edge deployment on robotic systems
Work with vendors to label data and build robust data extraction and labeling pipelines
Design custom metrics to evaluate model performance in the field
Reduce model latency using tools like ONNX, TensorRT, or similar
What we’re looking for:
Practical experience applying machine learning with deep learning frameworks, such as PyTorch, to solve real-world problems
Proficiency in Python and comfort with at least one systems language (e.g., C++, Rust)
Experience deploying ML models to robotic systems or other physical platforms
Experience incorporating raw sensor data like camera, lidar, radar, IMUs, etc into deep learning algorithms.
Bonus: Practical application of incorporating 3D geometry into deep learning models
Bonus: Published work in conferences such as ICRA, IROS, CoRL, CVPR, ECCV, ICCV, ICML, NeurIPS,
We’re especially interested in engineers who thrive at the intersection of ML research and real-world robotics applications.
Onboard Platform - Software Engineer
We are looking for exceptional software engineers to build across a range of areas and develop our onboard stack: high-performance data pipelines between sensors and models, middleware, fault injection, performance characterization, optimization, microsecond latency communication, and analytical tooling. Your code will be the beating heart of 40-ton machines building hospitals, roads, factories, data centers, and highways. You will dive deep to solve complex system-level issues, from subtle sensor data degradations to elusive performance bottlenecks in our estimation and control loops.
We code in modern system languages like Rust and C++14 and are looking for engineers who love to code and deeply understand systems. Ideal candidates are exceptional debuggers as well as software architects who take a first principles approach to problem solving. If you happen to have direct experience with safety-critical systems or standards like ISO26262, that’s a plus (but not required). Apply if any of this sounds great!
Cloud - Distributed Systems Engineer
Bedrock Robotics is transforming the physical world with autonomy. While others debate the future of AI, we're deploying it. With a team that helped put self-driving cars on public roads at Waymo, scaled systems for Segment's $3.2B acquisition, and grew Uber Freight to $5B in revenue, and with the backing of world-class advisors and investors from 8VC, Eclipse, Valor, Two Sigma, and many others, we are uniquely positioned to succeed in our optimistic vision of autonomy and industrial transformation.
We need you - exceptional autonomy is built on the highest scale and most complex infrastructure engineering. We are solving the challenges of scaled model training, data systems, observability, and real-time robotics.
As a passionate distributed systems engineer you will have immediate impact on the core mission, and will also work on novel problems at the intersection of infrastructure and robotics. We are looking for experienced software engineers / TLs at all stages of their career experienced in large scale distributed systems or big data.
Some of the challenges our team takes on include:
Build the foundation for large scale end to end model training.
Running inference of petabytes of video and lidar data.
Scaling out Simulation-based evaluation of our stack.
Building the Data platform that writes, indexes, queries, billions of metrics and labels.
Power semantic search and data analysis using state of the art VLMs.
Stream large amounts of data from robots operating across the US.
Enable hardware-in-the-loop testing and validation.
Also, you get to drive 100,000 lb excavators.
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