This role serves as the technical lead for AI/ML development on a fast-paced team prototyping new technologies
Our charter is to identify, test, develop and deploy new products to meet current and future operational challenges, and as an AI/ML Engineer III on our team, you will serve as the primary driver for AI/ML development projects focused on autonomy, perception systems, analytics developing rapid proof-of-concept builds and performing demonstrations.
This role requires not only advanced machine learning expertise, but also the ability to operate with high autonomy, set technical direction and develop technical requirements to meet high-level objectives, and mentor JTF Sierra engineers who are developing and growing their own AI/ML skillsets.
This role will bridge the gap between high-level vision provided by senior technology directors and help set & accomplish day-to-day execution performed alongside software, systems, and other subject matter experts. You will ensure that AI/ML efforts are technically sound, aligned with mission objectives, and deliverable within rapid R&D timelines.
Role Expectations Specific to This Team- Serve as primary day-to-day AI/ML expert & performer other team members are AI/ML learners or strategic-level advisors
- Rapidly define architecture, technical direction, and technical requirements for new AI/ML initiatives and prototypes without regular direct technical oversight
- Help Program Manager/Project Engineer identify staffing, tooling, and data required to accomplish new AI/ML prototypes, help advise and manage technical risks during execution
- Play a key role in shaping the entire organization s growing AI/ML capability over the next several years
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- 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.
- Translate high-level conceptual guidance from leadership into actionable requirements, designs, roadmaps, and technical approaches.
- Collaborate with other engineer functions, hardware teams, product subject matter experts, and data scientists to align AI/ML solutions with mission-specific requirements and constraints.
- Shape system-level behavior and technical tradeoffs for AI/ML prototypes when requirements are evolving or ambiguous.
- Architect and build end-to-end AI/ML prototypes quickly, including data ingestion, feature engineering, training pipelines, model deployment and evaluation.
- Work with Project Engineer/Project Manager to identify and manage technical risks, develop mitigation paths, and scope prototype schedule and manpower requirements.
- Coordinate with existing product engineering teams to integrate AI/ML prototype components into existing SNC products and/or larger autonomous systems and platforms.
- Develop and oversee robust validation and testing frameworks to ensure that AI/ML 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 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.
- Preparing & executing demonstration plans, technical briefings, and trade studies/case studies for leadership and program stakeholders
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- Ability to mentor and upskill engineers with limited or developing AI/ML backgrounds.
- Experience delivering rapid prototypes or research models under tight schedule pressure.
- Comfort working with incomplete information and shaping requirements through experimentation.
- Strong communication skills for translating complex AI concepts to non?AI specialists.
- Bachelor s degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
- 6 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 9 years of related experience is required.
- Higher level relevant degree may substitute for experience.
- Proficient in machine learning frameworks (e.g., TensorFlow, PyTorch) and skilled in implementing advanced AI/ML techniques, such as supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic), as well as working with generative AI models (e.g., transformers).
- Proficient in developing, deploying, and optimizing AI/ML models, including ANNs, CNNs, and RNNs, for production applications. Contributed to the design and scaling of systems for larger datasets or environments with moderate complexity.
- 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
Qualifications We Prefer - Experience building the AI/ML technical function of a small or maturing team.
- Familiarity with earlystage autonomy R&D efforts or multimodal sensor fusion research.
- Experience integrating ML models into embedded, realtime, or autonomous platforms.
- Demonstrated ability to establish ML engineering practices (MLOps, data versioning, model validation frameworks).
- Master s degree in Artificial Intelligence, Machine Learning, or related field.
- Experience leading teams or projects in aerospace and defense industries.
- Familiarity with cybersecurity and regulatory requirements.
- Proficient in Agile or DevOps workflows; active participant in iterative ML software development.
- Practical experience designing and implementing advanced ML techniques, such as clustering, dimensionality reduction, or generative modeling.
- Hands-on experience with GPU programming and using high-performance computing systems for ML workloads.
- Experience with at least one reinforcement learning or generative AI model (e.g., implementing GANs or Transformers).
- Able to analyze large-scale, heterogeneous datasets and apply advanced statistical and ML methods to real-world problems.
- Experience translating mission objectives into actionable system requirements, including HMI scenarios.
- Familiarity with hardware acceleration (e.g., CUDA, TensorRT) and introductory knowledge of edge AI or XAI.
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