Radar AI Engineer, Edge Deployment & Autonomy

Blue Origin; Reston (VA); On-site; USD 131,000 - 183,000; Full time

Benefits offered by this job

Relocation assistance

Travel up to 10%

TS/SCI clearance eligibility

Job summary

Blue Origin in Reston, VA is seeking an ML engineer to own the radar AI architecture on a new program. You will design, train and deploy models that classify objects and estimate attributes from radar data, with edge deployment constraints.

The role emphasizes working with cross-disciplinary teams to define data, metrics, and qualification for edge deployment, with relocation assistance and TS/SCI eligibility.

Qualifications

• BS in Computer Science, Electrical Engineering, Computer Engineering, Physics, or a related field.
• 3 years of ML engineering experience.

Responsibilities

• Design, train and evaluate deep learning models (GNNs, transformers, DRL, Learned Algorithm Unfolding or hybrids) that find and classify objects of interest in raw radar data as well as range-Doppler and range-angle maps.
• Build characterization models that estimate object attributes such as size, shape, motion state, track, behavior, with calibrated uncertainty.
• Represent radar data in the right form for each model, for example point or track graphs for GNNs.
• Build the data engine: synthetic data generation, simulation-based training, labeling strategy, augmentation, and handling of class imbalance.
• Detect inputs that fall outside the training data, and flag low-confidence results so downstream systems know when not to trust the model.
• Work with the Advanced Systems, DSP, GNC, and flight software teams to define how data is handed between stages and to deploy models on embedded or edge hardware.
• Define the metrics, test sets, and evidence needed to qualify ML models for deployment to the edge.

Skills

Deep learning

PyTorch

Python

Edge deployment

Radar fundamentals

Education

Bachelor's degree in STEM

Tools

TensorRT

FPGA

Job description

Blue Origin in Reston, VA is seeking an ML engineer to own the radar AI architecture on a new program. You will design, train and deploy models that classify objects and estimate attributes from radar data, with edge deployment constraints.

The role emphasizes working with cross-disciplinary teams to define data, metrics, and qualification for edge deployment, with relocation assistance and TS/SCI eligibility.