Senior AI/ML Engineer for Autonomous Systems

NLP PEOPLE; Lone Tree (CO); Hybrid; USD 125,000 - 172,000; Full time

Benefits offered by this job

Medical benefits

401(k) with match

Job summary

Sierra Nevada Corporation is seeking an AI/ML Engineer III to design, develop, and deploy advanced ML systems for aerospace and defense. You will lead autonomous system features, mentor engineers, and drive projects with mission-critical impact.

The role spans deep neural networks, reinforcement learning, transformers, and integration with existing software/hardware. Hybrid work, travel up to 10–20%, and a strong emphasis on validation and cybersecurity considerations are expected.

Qualifications

• Bachelor's degree in computer science or related STEM field; 6+ years in AI/ML, or 9 years without degree.
• Proficiency in ML frameworks (TensorFlow, PyTorch) and producing production AI/ML.
• Strong Python/C++/Java background with scalable AI/ML systems.
• Experience leading teams or projects and deploying models in production.
• Knowledge of regulatory and cybersecurity requirements for AI/ML in aerospace.

Responsibilities

• Lead design and development of ML models including deep networks and RL.
• Architect scalable AI/ML systems that integrate with existing hardware/software.
• Mentor junior engineers and manage AI/ML projects and timelines.
• Develop validation/testing frameworks for performance, safety, and compliance.
• Collaborate with systems/hardware teams to align AI with mission requirements.
• Train and optimize AI architectures (including transformers) for complex apps.
• Lead signal processing, computer vision, and planning algorithms for autonomy.

Skills

Python

C++

TensorFlow

PyTorch

Transformers

Reinforcement learning

Deep learning

MLOps

Leadership

Education

Bachelors in CS

Tools

CUDA

TensorRT

GPU Programming

Job description

Sierra Nevada Corporation is seeking an AI/ML Engineer III to design, develop, and deploy advanced ML systems for aerospace and defense. You will lead autonomous system features, mentor engineers, and drive projects with mission-critical impact.

The role spans deep neural networks, reinforcement learning, transformers, and integration with existing software/hardware. Hybrid work, travel up to 10–20%, and a strong emphasis on validation and cybersecurity considerations are expected.