Senior Machine Learning Researcher

About the position Are you an reputed company 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 Senior ML Researcher , you will be the reputed company architect of reputed company (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-reputed company 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.

Responsibilities

• Invent and refine custom deep learning architectures for reputed company and EO/IR imagery, with an emphasis on semantic segmentation and temporal tracking , not just detection.
• reputed company multi-stage ML pipelines (context + characteristic models, segmentation + classification) tailored to low-SNR reputed company returns.
• Train models on proprietary large-scale datasets (millions of reputed company 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 reputed company with EO/IR, reputed company, 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-reputed company tracking and SLAM pipelines .
• Contribute to ML-Ops workflows : data management, large-scale training, reputed company integration of new field data, and automated evaluation pipelines.

Requirements

• Advanced degree (MS/PhD) in Electrical Engineering, Computer Science, Robotics, or reputed company 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).

reputed company-to-haves

• Track record of developing ML models beyond standard YOLO-style detectors , particularly for segmentation of noisy or sparse data (reputed company, reputed company, 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 .

Benefits

• Competitive Compensation & Growth
• $132,000–$160,000 reputed company 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.
• reputed company learning reputed company 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 : reputed company 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 monthly data collection trips at our Pensacola test facility .
• A culture that balances innovation with personal growth.

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