Senior R&D Lead – AI / ML Engineer

We are seeking an accomplished Senior R&D Lead – AI / ML Engineer to spearhead the development and integration of advanced Artificial Intelligence solutions across our simulation platforms. This role demands deep domain expertise, strategic technology vision, and the ability to lead multidisciplinary engineering teams. The ideal candidate will architect next-gen AI / ML frameworks to enhance training realism, adaptability, and data-driven performance evaluation within military simulation systems.

Key Responsibilities

Lead end-to-end design, development, and integration of AI / ML models to enhance simulation realism, trainee behavior understanding, and adaptive training responses.

Develop Reinforcement Learning (RL) solutions for intelligent opponents, scenario adaptation, and real-time policy optimization.

Architect and deploy Deep Neural Network models using transformers, attention mechanisms, and multi-modal architectures (vision + language + decision).

Implement and optimize Large Language Models (LLMs) within relevant training and decision-support modules.

Ensure real-time performance, safety, and reliability of AI modules, especially under contested or adversarial simulation environments.

Uphold AI ethics, safety, and compliance with defense standards and autonomous systems regulations.

Design and maintain evaluation and scoring models to assess trainee progress based on behavioral, accuracy, and situational performance metrics.

Work closely with cross-functional hardware, software, simulation, and defense domain teams for seamless AI system integration.

Continuously assess emerging AI advancements and convert research outputs into production-grade solutions .

Lead and mentor a team of AI engineers, fostering an environment of innovation and technical excellence.

Oversee the data pipeline strategy – collection, annotation, preprocessing, and validation workflows.

Collaborate with Defense stakeholders, SMEs, and internal leadership to align technological development with operational requirements.

Required Qualifications

Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning , or related fields.

8+ years of hands-on experience in AI / ML , with strong expertise in Deep Learning, Reinforcement Learning, and Multi-Modal architectures .

Strong command of Neural Network architectures , including Transformers and attention-based models , and practical deployment experience with LLMs .

Proven experience implementing Reinforcement Learning algorithms , particularly in environments requiring real-time decisions and evaluative feedback loops .

Proficiency in Python , OpenCV , and frameworks such as PyTorch , TensorFlow , Stable Baselines3 , Ray RL , and OpenAI Gym / Gymnasium .

Experience in defense / military / aerospace / high-reliability simulation systems is highly desirable.

Demonstrated leadership ability in managing cross-functional engineering teams and delivering large-scale AI systems to production.

Strong analytical mindset with the ability to evaluate, benchmark, and optimize competing AI methodologies.

Preferred Attributes

Exposure to embedded ML in real-time training platforms.

Experience with tactical behavior modeling, sensor fusion, or agent-based simulation.

Publications, patents, or conference contributions in AI / ML.