Senior Staff Software Engineer, Perception (R4985)
Shield AI · Washington, D.C. ·
- Work mode
- Onsite
- Seniority
- Staff
- Employment
- Part time
- Category
- Software engineering
- Experience
- 7+ years
- Visa sponsorship
- Yes
- Company size
- 501-1000
Shield AI · Washington, D.C. ·
torcrobotics · Remote, U.S, Ann Arbor, MI, Fort Worth, TX, Blacksburg, VA
General Motors · GM Automation - Sunnyvale - GM Automation - Sunnyvale
Saildrone · Alameda, California, United States
Senior engineer builds and deploys cutting-edge vision, vision-language, and vision-language-action models for autonomous aircraft, turning research into production-ready perception systems for defense customers.
Model Development – Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems.
Data Pipelines & Model Training – Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks.
Model Deployment & Optimization – Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks.
Perception & Autonomy Applications – Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments.
Research-to-Production – Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability.
Cross-functional Collaboration – Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems.
Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements.
Continuous Improvement – Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery.
Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience.
Mastery of machine learning fundamentals.
Experience training an deploying ML models for computer vision in a production setting.
Strong understanding of 3D vision problems/algorithms.
Experience with machine learning frameworks such as PyTorch and TensorFlow.
Demonstrated expertise in deploying models using TensorRT and ONNX.
Proficiency in C++ and Python.
Strong analytical and problem-solving skills, with the ability to translate research into practical applications.
Experience with developing autonomous systems for defense customers.
Experience with training/finetuning vision-language models, vision-language-action models, and/or world models.
Contributions to open-source projects in machine learning or computer vision.
Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).
Latitude AI · Palo Alto, CA, Pittsburgh, PA, Detroit, MI, Remote
Latitude AI · Palo Alto, United States