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Staff Deep Learning Engineer, State Estimation (R5785)

Shield AI· Hivemind Enterprise Division – Engineering
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Remote$200k - $300kFull Time EmployeePosted 3w ago

About the role

Senior-level deep learning engineer focused on state estimation for autonomous systems within Shield AI’s Hivemind SDK, combining deep learning, 3D computer vision, and geometric estimation to enable vision-based localization when GPS is unavailable.

Responsibilities

  • Develop and evaluate models for tasks such as feature detection and matching, visual correspondence, depth estimation, relative pose estimation, and image-to-map localization.
  • Combine learned visual representations with geometric methods to improve localization accuracy, robustness, and recovery under challenging conditions.
  • Own data preparation and supervision strategies, including dataset curation, annotation requirements, labeling tools, automated quality checks, and coverage analysis.
  • Select and integrate deep learning tools and build reproducible training workflows, including experiment tracking, configuration management, and dataset and model versioning.
  • Design evaluations that measure both model performance and downstream localization outcomes across changes in lighting, viewpoint, altitude, terrain, weather, and sensor characteristics.
  • Analyze failures and use controlled experiments to prioritize improvements to data, supervision, models, and integration.
  • Partner with state estimation engineers to integrate learned measurements and confidence estimates into VIO and terrain-relative navigation systems.
  • Profile models against onboard compute, memory, and latency constraints, and work with deployment engineers on optimization and runtime validation.
  • Deliver tested, documented components and interfaces for Hivemind SDK, collaborating with software, systems, and flight test teams.

Qualifications

  • MS in Aerospace Engineering, Electrical Engineering, Robotics, Computer Science, or related field; 4+ years with MS, or 2+ years with PhD
  • Hands-on experience designing, training, debugging, and evaluating models using PyTorch or equivalent framework, including architecture selection, loss design, optimization, and augmentation that preserves geometric consistency
  • Strong foundations in camera models, coordinate transformations, projective geometry, and multi-view geometry with practical experience in vision-based navigation, visual geolocation, SfM, SLAM, 3D reconstruction, depth estimation or similar
  • Strong Python skills and experience writing maintainable, reusable software; ability to take a CV capability from problem definition to deployment readiness
  • Experience building pipelines for sensor data ingestion, cleaning, filtering, deduplication, and dataset versioning
  • Ability to design reproducible training workflows, including configuration management, experiment tracking, checkpointing, and GPU performance troubleshooting
  • Experience designing benchmarks, preventing data leakage, analyzing performance across operating conditions, and connecting model metrics to downstream localization accuracy
  • Ability to profile inference latency and memory use, document model interfaces and preprocessing, assess accuracy–compute tradeoffs, and advise on export, precision, and runtime optimization
  • Ability to communicate assumptions, experimental findings, and design tradeoffs clearly and translate research into working software

Skills

Required:Deep learning model development3D computer vision and geometryPython

Benefits

  • Pay within range listed + Bonus + Benefits + Equity
  • Temporary employee offer package with temporary benefits after 60 days of employment
  • Salary compensation influenced by multiple factors; offers contingent on cleared background and reference checks; military fellows and part-time employees not eligible for benefits
Last updated Oct 23, 2026. Interested? Apply on the company site.

About Shield AI

Autonomy for the world.

Our mission is to protect service members and civilians with intelligent systems.

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