AI/ML Engineer

• 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

• 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.