Senior Machine Learning Engineer
$130,000–$162,000 year
On-siteBirmingham, Alabama, United States
Job Summary
Design custom deep learning architectures for radar and EO/IR imagery, focusing on semantic segmentation and temporal tracking for maritime autonomy. Develop multi-stage ML pipelines tailored to low-SNR radar returns and train models on proprietary large-scale datasets using design-of-experiment methods. Optimize and deploy models to resource-constrained edge hardware, including C++ inference layers, while collaborating on fusion-aware systems that integrate radar with EO/IR, AIS, and cartography. Manage ML-Ops workflows covering data management, large-scale training, and automated evaluation pipelines. This role defines the perception stack for defense USVs/ASVs and commercial marine ADAS, requiring hands-on field validation at the Pensacola test facility.
Required Qualifications
- Advanced degree (MS/PhD) in Electrical Engineering, Computer Science, Robotics, or related field
- 7+ years applying machine learning and signal processing to real-world dynamic systems (graduate research counts if directly applicable)
- Demonstrated mastery of semantic segmentation and object classification models, ideally applied to non-vision sensor modalities
- Expert-level Python skills with ML frameworks (TensorFlow/Keras, PyTorch, or equivalent)
- Full-time, in person Birmingham (AL)
- All employees must be eligible to obtain a U.S. Department of Defense security clearance
- With few exceptions, this is restricted to U.S. citizens and legal permanent residents (a.k.a. current Green Card Holders)
Desired Qualifications
- Track record of developing ML models beyond standard YOLO-style detectors, particularly for segmentation of noisy or sparse data (Radar, sonar, or medical imaging)
- Strong background in computer vision and temporal modeling (CNNs, transformers, RNNs for sequential sensor data)
- Experience deploying ML to embedded/edge platforms with optimized C++ inference
- Knowledge of marine, automotive, or aerial robotics systems
- Contributions to large-scale ML data pipelines: annotation strategies, dataset balancing, simulation-to-real transfer
- Passion for pushing the boundaries of AI in GPS-denied, cluttered, and low-visibility environments
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