Senior Machine Learning Engineer

Tocaro BlueBirmingham, AL
Onsite

About The Position

Transform Maritime Intelligence with Cutting-Edge AI/ML. At Tocaro Blue, your expertise in designing, training, and deploying custom ML models will directly advance our foundational perception stack, ProteusCore radar tracking and ApolloCore radar/camera fusion. As a Senior Machine Learning Engineer, you will build ML 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. You will be responsible for organizing dataset design, data collection in real and simulated environments, and synthetic augmentation of radar and camera datasets. Your work will fuel products used by Defense customers developing USVs/ASVs for the U.S. Navy and 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.

Requirements

  • 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)

Nice To Haves

  • 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

Responsibilities

  • 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

Benefits

  • Competitive 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
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