Machine Learning Engineer, Radar Perception II/III

Blue Origin•Littleton, CO

1d•$119,814 - $182,988

About The Position

Blue Origin is hiring a Machine Learning Engineer for its Blue National Security Autonomy & Intelligent Mission Products organization. The role focuses on developing the AI layer that processes raw radar data, identifies objects of interest, and characterizes them so that an autonomy stack or operator can act on the results. This is a new development program where the engineer will help define the model architecture. The work addresses limited labeled data, constrained hardware resources, and demanding deployment requirements for national security missions. The engineer will design, train, and evaluate models for radar object detection, classification, and characterization; build data-generation and training workflows; assess uncertainty and out-of-distribution inputs; and collaborate with systems, signal-processing, guidance, navigation and control, and flight-software teams to integrate models onto embedded or edge hardware. The position is an individual contributor role, with travel of up to 10% and relocation assistance available. The successful candidate must be able to obtain a TS/SCI clearance.

Requirements

Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, Physics, or a related field.
About 3 years of machine learning engineering experience.
Track record of building and shipping deep learning models in PyTorch or a similar framework.
Experience with edge deployment, such as TensorRT, quantization, FPGA, or SoC targets.
Strong Python skills.
Working knowledge of radar fundamentals, including range, Doppler, angle, resolution, clutter, and multipath.
Ability to obtain a TS/SCI clearance.
U.S. citizenship or nationality, U.S. permanent residency, or lawful admission to the U.S. as a refugee or grant of asylum.
Successful completion of Blue Origin’s standard background check.

Nice To Haves

Familiarity with Ground Moving Target Indicator (GMTI) or Airborne Moving Target Indicator (AMTI) signal-processing concepts and their implications for system design.
Experience with sensor data from radar, sonar, SAR, lidar, or RF.
Experience training on synthetic or simulated data and closing the gap between simulation and real data.
Experience with uncertainty quantification, calibration, or out-of-distribution detection.
Experience with embedded C++.
Active TS/SCI clearance.

Responsibilities

Design, train, and evaluate deep learning models, including GNNs, transformers, deep reinforcement learning, learned algorithm unfolding, or hybrid approaches, to find and classify objects in raw radar data and range-Doppler and range-angle maps.
Build models to estimate object attributes such as size, shape, motion state, track, and behavior, with calibrated uncertainty.
Represent radar data in suitable forms for each model, such as point or track graphs for GNNs.
Build the data engine, including synthetic data generation, simulation-based training, labeling strategy, augmentation, and handling class imbalance.
Detect inputs outside the training distribution and flag low-confidence results for downstream systems.
Work with Advanced Systems, DSP, GNC, and flight-software teams to define data handoffs and deploy models on embedded or edge hardware.
Define metrics, test sets, and evidence required to qualify ML models for edge deployment.

Benefits

Medical insurance
Dental insurance
Vision insurance
Basic and supplemental life insurance
Paid parental leave
Short- and long-term disability
401(k) with company match of up to 5%
Education Support Program
Stock options for regular employees working at least 20 hours per week
Up to four weeks of paid time off per year based on weekly scheduled hours
Up to 14 company-paid holidays
Depending on role type and job level, potential eligibility for benefits and bonuses based on individual contributions and company results