AI​/ML Engineer III

Role Overview

This role serves as the technical lead for AI/ML development on a fast‑paced team prototyping new technologies for Sierra Nevada Company’s Joint Task Force (JTF) Sierra. The charter is to identify, test, develop and deploy new products to address current and future operational challenges. As an AI/ML Engineer III, you will be the primary driver for AI/ML projects focused on autonomy, perception systems, analytics, rapid proof‑of‑concept builds, and demonstrations.

The role requires advanced machine learning expertise, high autonomy, the ability to set technical direction and develop requirements to meet high‑level objectives, and mentorship of SNC engineers in AI/ML practices.

• Serve as the primary day‑to‑day AI/ML expert and performer on the team.
• Rapidly define architecture, technical direction, and technical requirements for new AI/ML initiatives and prototypes without regular direct oversight.
• Help the Program Manager/Project Engineer identify staffing, tooling, and data needed for new AI/ML prototypes, advise on and manage technical risks during execution.
• Play a key role in shaping the organization’s evolving AI/ML capability.

• Lead the design and development of advanced machine learning models, including deep neural networks, reinforcement learning systems, and generative AI algorithms.
• Architect scalable AI/ML systems that integrate seamlessly with existing software and hardware platforms.
• Provide guidance on selecting tools, frameworks, and infrastructure.
• Translate high‑level guidance from leadership into actionable requirements, designs, roadmaps, and technical approaches.
• Collaborate with hardware teams, product subject‑matter experts, and data scientists to align AI/ML solutions with mission‑specific requirements.
• Shape system‑level behavior and tradeoffs for AI/ML prototypes when requirements are evolving or ambiguous.
• Build end‑to‑end AI/ML prototypes quickly, including data ingestion, feature engineering, training pipelines, model deployment, and evaluation.
• Work with the Project Engineer/Project Manager to identify and manage technical risks, develop mitigation paths, and scope prototype schedule and manpower.
• Coordinate with existing product engineering teams to integrate AI/ML prototype components into existing SNC products or larger autonomous systems.
• Develop and oversee robust validation and testing frameworks to ensure models meet performance, safety, and compliance standards in real‑world scenarios.
• Coach engineering peers, providing technical guidance and fostering a collaborative, innovative team environment.
• Stay current with emerging AI/ML technologies and propose innovative solutions to address new and existing challenges in aerospace and defense.
• Communicate technical concepts, project progress, and outcomes to stakeholders, including leadership and external partners.
• Independently train, fine‑tune, and optimize advanced AI architectures such as transformers for complex applications.
• Apply a broad range of AI/ML techniques—including supervised, unsupervised, reinforcement, and generative learning—to solve domain‑specific challenges.
• Lead the development and integration of signal processing, computer vision, and planning algorithms to advance autonomous system functionality.
• Design and execute large‑scale simulations and modeling of AI/ML systems, ensuring scalability and robustness on CPU/GPU platforms.

• Minimum 6 years of experience delivering rapid prototypes or research models under tight schedule pressure.
• Comfortable working with incomplete information and shaping requirements through experimentation.
• Strong communication skills for translating complex AI concepts to non‑AI specialists.
• Ability to mentor and up‑skill engineers with limited or developing AI/ML backgrounds.
• Bachelor’s degree in computer science, mathematics, statistics, engineering, or a related STEM discipline (equivalent experience may substitute; 9 years experience if no degree).
• Proficiency with machine learning frameworks such as Tensor Flow or PyTorch and advanced AI/ML techniques, including supervised, unsupervised, reinforcement learning (e.g., PPO,…