Sr. AI Engineer

Sierra Nevada Corporation•Lone Tree, CO

1d•$143,487 - $197,295•Hybrid

About The Position

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading the development of complex AI/ML systems, driving innovation, and mentoring team members to deliver impactful solutions. In this role, you will oversee the design, implementation, and deployment of scalable AI/ML models for mission-critical aerospace and defense applications. You will also act as a technical leader, providing strategic guidance on AI/ML initiatives, ensuring compliance with regulatory standards, and collaborating with stakeholders to meet organizational objectives. This position demands advanced technical expertise and the ability to manage high-impact projects in a fast-paced environment. The ISR (Intelligence, Surveillance & Reconnaissance), Aviation, and Security (IAS) business area is a leader in ISR and aviation, it is a leading prime manned and unmanned aircraft systems integrator for innovative, high-performance ISR and aviation systems. Its end-to-end Command, Control, Computers, Communications and Intelligence, Surveillance & Reconnaissance (C4ISR) capabilities encompass design, integration, test, certification, ground/flight training and complete logistics support. IAS tailors solutions to customer cost, performance, and schedule requirements and designs to consistently exceed expectations – with an unrivaled record of on time and on (or under) budget deliveries.

Requirements

Bachelor’s degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
10+ years of experience in a related field.
Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 12 years of related experience is required.
Higher level relevant degree may substitute for experience.
Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques, including supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic).
Demonstrated ability to design and optimize generative AI models (e.g., transformers) and neural networks for complex applications.
Extensive experience architecting, deploying, and optimizing AI/ML systems, including ANNs, CNNs, and RNNs, in large-scale or mission-critical environments.
Led efforts to improve model performance and reliability in production settings.
Strong proficiency in programming languages such as Python, C++, C# or Java, with experience in building scalable AI/ML systems.
Demonstrated experience leading teams or projects, including mentoring junior staff.
Proven track record of deploying AI/ML models in production environments and optimizing them for real-world use cases.
Knowledge of regulatory and cybersecurity requirements for AI/ML systems in aerospace and defense applications.
Active Secret US Security Clearance

Nice To Haves

Master's degree + additional years experience, or Ph.D. in Artificial Intelligence, Machine Learning, or a related field.
Experience with hardware acceleration technologies (e.g., CUDA, TensorRT) and high-performance computing systems.
Background in autonomous systems, robotics, or sensor fusion.
Familiarity with Agile/DevOps methodologies for software development.
Certifications in AI/ML or related fields, such as AWS Certified Machine Learning Specialty or Google Professional Machine Learning Engineer.
Deep understanding and practical application of Agile/DevOps in large-scale AI/ML projects.
Demonstrated experience with reinforcement learning and generative AI models in production or research settings.
Advanced proficiency in GPU programming, parallel/distributed computing, and optimizing ML workloads for performance.
Expertise in designing and implementing complex ML pipelines, including clustering, dimensionality reduction, generative modeling, and reinforcement learning, aligned to mission objectives and HMI systems.
Skilled in analyzing massive, multi-source datasets and delivering end-to-end autonomy software solutions, from requirements to deployment and maintenance.
Working knowledge of hardware acceleration technologies (CUDA, TensorRT), edge AI deployments, and explainable AI (XAI) methods.
Exposure to or interest in quantum computing for ML applications.

Responsibilities

Lead the design and development of advanced machine learning models, including deep neural networks, reinforcement learning systems, and generative AI algorithms, to solve complex problems.
Architect scalable AI/ML systems that can integrate seamlessly with existing software and hardware platforms.
Provide guidance on the selection of tools, frameworks, and infrastructure.
Collaborate with systems engineers, hardware teams, and data scientists to align AI/ML solutions with mission-specific requirements and constraints.
Manage AI/ML projects, including scoping, resource allocation, and timeline management, ensuring that deliverables meet quality and performance expectations.
Develop and oversee robust validation and testing frameworks to ensure that AI/ML models meet performance, safety, and compliance standards in real-world scenarios.
Mentor junior engineers, 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 the aerospace and defense domain.
Communicate technical concepts, project progress, and outcomes to stakeholders, including leadership and external partners, in a clear and concise manner.
Independently train, fine-tune, and optimize advanced AI architectures (including transformers) for complex applications.
Apply a broad range of AI/ML techniques (supervised, unsupervised, reinforcement, generative) 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, performance, and robustness on CPU/GPU platforms.
Lead rigorous validation and verification activities, ensuring deliverables meet performance, safety, and reliability requirements.
Lead and manage AI/ML projects, including end-to-end development and deployment.
Collaborate with cross-functional teams and oversee the integration of AI/ML systems into complex aerospace platforms.
Ensure compliance with safety, regulatory, and cybersecurity standards for AI/ML systems.