Senior Staff Software Engineer, Perception (R4985)

Team: Flight System Integration

Location: Washington, DC, Dallas, Texas, San Diego, California, Boston, MA

Commitment: Full Time Employee

Workplace Type: onsite

What You'll Do:

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. 

Required Qualifications:

• 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. 

• Ability to obtain a SECRET clearance 

Preferred Qualifications:

• 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).