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Staff Deep Learning Engineer, State Estimation (R5785)

Shield AIRemotePilot
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Salary
Not listed
Job type
Full Time Employee
Work mode
Remote
Experience
Senior · 2+ yrs
Posted
26 Sept 2026
Status
Open · checked 7d ago

About this role

The Staff Deep Learning Engineer, State Estimation role at Shield AI is a remote, full-time position focused on building deep learning capabilities for autonomous systems to navigate without GPS. This position suits specialists with a background in deep learning, 3D computer vision, and geometric estimation who want to develop navigation technology for aircraft.

Role Overview

Shield AI seeks a Staff Deep Learning Engineer to join the Hivemind SDK State Estimation and Vision team. The professional in this position builds learned components that help autonomous systems understand their motion and localize when GPS is unavailable. Responsibilities span the complete model development lifecycle, from tool selection and data curation to training, evaluation, and deployment support.

Key Responsibilities

Develop and evaluate models for tasks including feature detection and matching, visual correspondence, depth estimation, relative pose estimation, and image-to-map localization.
Combine learned visual representations with geometric methods to enhance localization accuracy and robustness under challenging conditions.
Manage data preparation and supervision strategies, covering dataset curation, annotation requirements, labeling tools, automated quality checks, and coverage analysis.
Build reproducible training workflows with experiment tracking, configuration management, and dataset and model versioning.
Design evaluations measuring model performance and downstream localization outcomes across varying lighting, viewpoints, altitudes, terrain, weather, and sensor traits.
Analyze failures through controlled experiments to improve data, supervision, models, and integration.
Collaborate with state estimation engineers to integrate learned measurements into VIO and terrain-relative navigation systems.
Profile models against onboard compute, memory, and latency constraints while supporting deployment engineers on optimization and runtime validation.
Deliver tested and documented components and interfaces for the Hivemind SDK.

Requirements

Master of Science degree in Aerospace Engineering, Electrical Engineering, Robotics, Computer Science, or a related field with at least four years of related professional experience, or a Ph.D. with at least two years of related experience.
Hands-on experience designing, training, debugging, and evaluating models using PyTorch or an equivalent framework.
Foundations in camera models, coordinate transformations, projective geometry, and multi-view geometry, paired with practical experience in vision-based navigation, visual geolocation, Structure from Motion, SLAM, 3D reconstruction, or depth estimation.
Python proficiency with the ability to take a computer vision capability from problem definition through deployment readiness.
Experience building pipelines for sensor data ingestion, cleaning, filtering, deduplication, and dataset versioning.
Ability to select development tools, manage configurations, track experiments, and handle GPU performance troubleshooting.
Experience designing benchmarks, preventing data leakage, and connecting model metrics to localization accuracy.
Ability to profile inference latency and memory use, document interfaces, and advise on runtime optimization.

Nice to Have

Experience with aerial imagery, geospatial data, elevation maps, or matching observations across varying viewpoints, lighting, seasons, or sensor modalities.
Experience with model export, quantization, TensorRT, ONNX, or deployment on embedded compute platforms.
Experience validating perception or robotics systems on physical platforms.
Relevant publications, open-source contributions, or demonstrated delivery of production computer vision systems.
Experience in the aerospace or defense industry.

Skills and Tools

PyTorch
Python
TensorRT
ONNX
Hivemind SDK

Salary and Benefits

Compensation includes pay within the listed range, a bonus, benefits, and equity for full-time regular employees.
Salary is determined by skill set, level of experience, licenses, certifications, and work location.

About the Company

Shield AI is a venture-backed defense-tech company that builds intelligent systems to protect service members and civilians. Its technology portfolio features Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. The company maintains offices and facilities across the United States, Europe, the Middle East, and Asia-Pacific.

How to Apply

Candidates should apply on the official company careers page.

Skills and tech stack

PyTorchPythonTensorRTONNXComputer VisionDeep LearningDiffusion

Questions candidates ask

What is the primary focus of the Staff Deep Learning Engineer?

The engineer builds deep learning capabilities that help autonomous systems understand their motion and localize when GPS is unavailable.

What educational and experience qualifications are required?

Candidates need an M.S. in Aerospace Engineering, Electrical Engineering, Robotics, Computer Science, or a related field with at least 4 years of experience, or a Ph.D. with at least 2 years of experience.

Is prior experience in vision-based navigation mandatory?

No, hands-on experience with deep learning and 3D computer vision and geometry is required, but prior experience specifically in vision-based navigation is optional.

Where is the position located?

This is a remote position.

What framework is required for model development?

Hands-on experience using PyTorch or an equivalent framework is required.

Ready to apply?

The application is on the official Shield AI careers page.

Apply on company site