Staff Deep Learning Engineer, State Estimation (R5785)

5 hours, 36 minutes ago
Full-time
Lead
Software Development
Bitly

Bitly

Bitly is a link management platform offering URL shortening, QR codes, and a Link in Bio solution for brands to optimize customer experience.

Internet Software & Services
51-250
Founded 2008
$92M raised

Description

  • Develop and evaluate models for feature matching, depth estimation, relative pose estimation, and image-to-map localization.
  • Combine learned visual representations with geometric methods to improve localization accuracy and robustness.
  • Own data preparation, annotation strategies, dataset curation, quality checks, and coverage analysis.
  • Select tools and build reproducible training workflows with experiment tracking and dataset/model versioning.
  • Design evaluations across varied lighting, viewpoints, terrain, weather, altitude, and sensor conditions.
  • Analyze failures and prioritize improvements through controlled experiments.
  • Integrate learned measurements and confidence estimates into VIO and terrain-relative navigation systems.
  • Profile models for onboard compute, memory, and latency constraints and support deployment optimization.
  • Deliver tested, documented Hivemind SDK components while collaborating with software, systems, and flight-test teams.

Requirements

  • M.S. in aerospace engineering, electrical engineering, robotics, computer science, or a related field, with 4+ years of related experience; or a Ph.D. with 2+ years of experience.
  • Hands-on experience designing, training, debugging, and evaluating deep learning models using PyTorch or an equivalent framework.
  • Strong knowledge of camera models, coordinate transformations, projective geometry, and multi-view geometry.
  • Experience with vision-based navigation, visual geolocation, SfM, SLAM, 3D reconstruction, depth estimation, or related fields.
  • Strong Python skills and experience developing maintainable, reusable software.
  • Experience building sensor-data pipelines for cleaning, filtering, deduplication, and dataset versioning.
  • Experience creating reproducible training workflows with configuration management, experiment tracking, checkpointing, and GPU troubleshooting.
  • Experience designing benchmarks, preventing data leakage, and connecting model metrics to downstream localization accuracy.
  • Ability to profile inference latency and memory use and assess accuracy–compute tradeoffs.
  • Preferred experience with aerial or geospatial data, embedded deployment, TensorRT, ONNX, quantization, physical robotics platforms, production computer vision, or aerospace/defense systems.

Benefits

  • Salary within the listed range plus bonus, benefits, and equity for full-time employees.
  • Temporary employees receive pay within the listed range plus temporary benefits after 60 days.
  • Benefits eligibility varies by employment type; military fellows and part-time employees are not eligible.
  • Offers are contingent on a cleared background and possible reference check.

Interested in this position?

Apply directly on the company website

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