Principle Machine Learning Engineer

Tocaro Blue

$140K — $200K *
Aerospace & Defense
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Advanced degree (MS/PhD) in Electrical Engineering, Computer Science, Robotics, or related field
  • 7+ years of experience in machine learning and signal processing for dynamic systems
  • Expertise in semantic segmentation and object classification models for non-vision sensor modalities
  • Expert-level Python skills with ML frameworks (e.g., TensorFlow/Keras, PyTorch)
  • Preferred: Experience developing models for noisy or sparse data, particularly in Radar or sonar.

Responsibilities

  • Lead the architecture of Radar and EO/IR models for object detection and tracking
  • Invent custom deep learning architectures with a focus on semantic segmentation
  • Develop multi-stage ML pipelines for low-SNR Radar data
  • Train models using proprietary large-scale datasets
  • Optimize and deploy models on resource-constrained edge hardware
  • Collaborate with engineers to integrate ML outputs into tracking and SLAM pipelines
  • Contribute to ML-Ops workflows for data management and training.

Benefits

  • 401(k) with 4% company matching
  • Full health, dental, and vision insurance
  • Generous PTO
  • Opportunities for continuous learning through conferences and training
  • Flexible work environment with hybrid and remote options.
Full Job Description
Job Description

Principle Machine Learning Engineer

Location: Southeastern United States (Hybrid/Remote)
Transform Maritime Intelligence with Cutting-Edge AI/ML

Are you an experienced machine learning researcher ready to push the limits of AI in one of the toughest domains-maritime autonomy? At Tocaro Blue, your expertise in designing, training, and deploying custom ML models will directly advance our foundational perception stack, ProteusCore.

As a Principal ML Engineer, you will be the lead architect of Radar (and secondary EO/IR) models for object detection, semantic segmentation, and tracking. You'll design algorithms capable of distinguishing vessels, land, shoreline constructions, wakes, and markers in dynamic maritime environments where off-the-shelf models fall short.

Your work will fuel products used by:
Defense customers developing USVs/ASVs for the U.S. Navy.
Commercial OEMs bringing advanced marine ADAS and autopilot features to market.

This role is an opportunity to define the ML foundations of maritime autonomy-where perception evolves from situational awareness, to navigation assistance, to full autonomy.
What You'll Pioneer

Core ML and Autonomy Innovation
• Invent and refine custom deep learning architectures for Radar and EO/IR imagery, with an emphasis on semantic segmentation and temporal tracking
• Develop multi-stage ML pipelines (context + characteristic models, segmentation + classification) tailored to low-SNR Radar returns
• Train models on proprietary large-scale datasets (millions of Radar samples and camera sequences) with design-of-experiment methods for data collection and annotation
• Optimize and deploy models to resource-constrained edge hardware (CPU-only and ARM64 platforms), including C++ inference layers
• Advance fusion-aware ML models that integrate Radar with EO/IR, AIS, and cartography for robust classification in GPS-denied or cluttered environments
• Collaborate with fusion and autonomy engineers to ensure ML outputs integrate seamlessly into multi-target tracking and SLAM pipelines
• Contribute to ML-Ops workflows: data management, large-scale training, continuous integration of new field data, and automated evaluation pipelines
What Sets You Apart

Essential 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)

Preferred Expertise
• 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
Why Tocaro Blue?

Competitive Compensation & Growth
• $140,000 - $200,000 base salary with potential equity in a rapidly growing company
• Comprehensive benefits: 401(k) with 4% company matching, full health/dental/vision, life & disability insurance, generous PTO
• Continuous learning via conferences, training, and professional growth

Innovation-First Culture
• Direct impact on defining the AI backbone of maritime autonomy
• Work on problems unsolved in automotive AI: Radar segmentation, maritime multi-object tracking, sensor fusion in GPS-denied waters
• Collaborative environment with elite engineers and researchers

Flexible Work Environment
• Hybrid and remote options for Southeastern US-based candidates. Offices in Pensacola (FL), Birmingham (AL), and Atlanta (GA)
• Hands-on field validation through semi-monthly data collection trips at our Pensacola test facility
• A culture that balances innovation with personal growth

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