Staff Deep Learning Engineer, State Estimation

🔥 25 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

👻 Ghost score 12%

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Shield AI

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2015

🤖 Artificial Intelligence

🚀 Aerospace

🎖️ Defense

Artificial Intelligence • Aerospace • Defense

Shield AI is a leading developer of AI-driven military solutions, focusing on enhancing mission autonomy and battlefield awareness. Their platform, Hivemind, enables rapid deployment of intelligent systems for various defense applications, including drone operation and surveillance. With a commitment to utilizing advanced technology, Shield AI aims to protect service members and civilians by revolutionizing defense technologies through autonomous systems.

📋 Description

• Develop and evaluate deep learning models for 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 • 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 with experiment tracking, configuration management, and dataset/model versioning • Design evaluations of model performance and downstream localization outcomes across lighting, viewpoint, altitude, terrain, weather, and sensor changes • Analyze failures and use controlled experiments to prioritize improvements • 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 • Work with deployment engineers on optimization and runtime validation • Deliver tested and documented Hivemind SDK components and interfaces • Collaborate with software, systems, and flight test teams

🎯 Requirements

• M.S. in Aerospace Engineering, Electrical Engineering, Robotics, Computer Science, or a related field • Minimum 4+ years of related professional work experience with an M.S. degree, or 2+ years with a Ph.D. • Hands-on experience designing, training, debugging, and evaluating models using PyTorch or an equivalent framework • Experience with architecture selection, loss design, optimization, and augmentation preserving geometric consistency • Strong foundations in camera models, coordinate transformations, projective geometry, and multi-view geometry • Practical experience in vision-based navigation, visual geolocation, Structure from Motion (SfM), SLAM, 3D reconstruction, depth estimation, or similar fields • Strong Python skills and experience writing maintainable, reusable software • Experience taking computer vision capabilities from problem definition and raw data through training, evaluation, and integration readiness • Experience building pipelines for sensor data ingestion, cleaning, filtering, deduplication, and dataset versioning • Ability to select and integrate development tools and build reproducible training workflows • Experience with 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 geometric or localization accuracy • Ability to profile inference latency and memory use, document model interfaces and preprocessing, assess accuracy–compute tradeoffs, and advise on deployment optimization • Ability to communicate assumptions, experimental findings, and design tradeoffs clearly and translate research into working software • All offers contingent on a cleared background and possible reference check • Preferred: experience with aerial imagery, geospatial data, elevation maps, or cross-condition/multimodal matching • Preferred: model export, quantization, TensorRT, ONNX, or embedded compute experience • Preferred: validating perception or robotics systems on physical platforms • Preferred: relevant publications, open-source contributions, or production computer vision systems • Preferred: experience with feature correlation, cost volumes, matching methods, learned geometry/depth/motion/appearance priors, diffusion models, or flow matching • Preferred: aerospace and/or defense industry experience • Ability to work in the United States / authorization to work in the United States addressed in the application form • Potential access to export-controlled information requiring U.S. citizenship, U.S. lawful permanent residency, protected individual status, or other qualifying status

🏖️ Benefits

• Bonus • Benefits • Equity • Temporary benefits package applicable after 60 days of employment (for temporary employees) • Full-time regular employee offer package • Cleared background and possible reference check contingent offer process

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