A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
Varstaff is looking for an AI/ML Engineer III . About the Job In this role, you will serve as the technical lead and primary driver for AI/ML development on a fast-paced prototyping team (Sierra Nevada Company's Joint Task Force Sierra - JTF Sierra). You will bridge the gap between high-level vision from technology directors and day-to-day execution, driving rapid proof-of-concept builds, demonstrations, and prototypes focused on autonomy, perception systems, and analytics. As the primary AI/ML expert on the team, you will set technical direction, define architecture and requirements without regular direct oversight, manage technical risks, mentor growing engineers, and shape the organization's long-term AI/ML capabilities. What We're Looking For Education & Experience Bachelor's degree in Computer Science, Mathematics, Applied Statistics, or a related STEM discipline plus 6+ years of related experience.
In lieu of a degree:
A minimum of 9+ years of related experience is required. Higher-level degrees may substitute for years of experience. Ability to mentor, coach, and "upskill" engineers with developing AI/ML backgrounds. Proven experience delivering rapid prototypes or research models under tight schedule pressure and comfort working with evolving, ambiguous requirements.
Must-Have Skills Technical Expertise:
Advanced machine learning proficiency across supervised, unsupervised, reinforcement (e.g., PPO, Actor/Critic), and generative AI models (e.g., transformers).
Frameworks & Languages:
Strong proficiency in Python, C++, C#, or Java, along with ML frameworks like TensorFlow or PyTorch.
Architecture & Deployment:
Hands-on experience architecting end-to-end ML systems (ANNs, CNNs, RNNs), data pipelines, training, model deployment, optimization, and evaluation.
Domain Applications:
Experience with signal processing, computer vision, and planning algorithms to advance autonomous system functionality.
Leadership & Execution:
Proven track record leading projects, shaping technical tradeoffs, managing technical risks, establishing validation frameworks, and preparing briefings/trade studies for stakeholders. Nice-to-Have Skills (Preferred) Master's degree in Artificial Intelligence, Machine Learning, or a related field. Experience building or scaling an AI/ML function within a small or maturing team. Background in Aerospace & Defense industries, including knowledge of cybersecurity, regulatory requirements, or edge AI/hardware acceleration (e.g., CUDA, TensorRT). Experience integrating ML models into embedded, real-time, or autonomous platforms, plus familiarity with multimodal sensor fusion. Hands-on experience with MLOps, GPU programming, high-performance computing, and Agile/DevOps workflows.
