Al/ML Engineer Technical Lead - TS/SCI w Poly
Role details
Job location
Tech stack
Job description
We are seeking a highly skilled AI/ML Engineer Technology Lead to design, development, and deployment of advanced Artificial Intelligence and Machine Learning solutions supporting mission-critical enterprise initiatives. This role serves as the technical lead for enterprise AI/ML efforts, responsible for building, growing, and guiding a team of AI/ML engineering and practitioners. This individual collaborates with customer technical leadership to define and realize their AI/ML roadmap and is expected to bring both deep technical expertise and the business acumen necessary to develop strategy, manage stakeholder relationships, and scale a high-performing team.
The ideal candidate combines deep expertise in machine learning, software engineering, cloud-native technologies, and MLOps with strong leadership and customer engagement skills. This individual will help transform AI/ML prototypes into scalable, secure, production-ready enterprise solutions while mentoring technical teams and collaborating with customer leadership. Key Responsibilities - AI/ML Technical Leadership Technical Leadership & Strategy Serve as the primary point of contact (POC) for all AI/ML-related technical matters with customers and stakeholders
- Lead the design, development, testing, deployment, and productization of AI/ML technologies supporting mission-critical objectives
- Develop and communicate AI/ML strategies and technical roadmaps aligned with customer and mission requirements
- Advise leadership on emerging AI/ML technologies, research areas, and industry advancements
- Represent AI/ML capabilities during customer engagements, briefings, demonstrations, and technical reviews
- Provide technical leadership, mentorship, and guidance to AI/ML engineering teams
- Support workforce planning, staffing strategy, hiring, and professional development initiatives
AI/ML Engineering & Development
- Design, develop, and optimize scalable machine learning and deep learning models for structured and unstructured data
- Transform research prototypes into secure, scalable, production-ready enterprise solutions
- Support NLP, predictive analytics, anomaly detection, computer vision, and generative AI initiatives
- Evaluate and productize AI/ML models across commercial and government cloud architectures
- Integrate AI/ML solutions across enterprise systems, data platforms, and operational environments
- Ensure AI/ML solutions meet performance, scalability, reliability, and operational requirements
Cloud, MLOps & Enterprise Integration
- Develop production-grade AI/ML pipelines, CI/CD workflows, and MLOps capabilities
- Provide system integration oversight across AI/ML pipelines and enterprise platforms
- Collaborate with software engineers, cloud architects, cybersecurity teams, and customer stakeholders
- Support deployment and optimization of AI/ML solutions across cloud-native and distributed environments
- Evaluate emerging technologies and align technical solutions with operational and enterprise objectives
Requirements
Core Competencies
- AI/ML Technical Leadership
- Cloud & Enterprise Architecture
- MLOps & Production AI Systems
- Team Building & Mentorship
- Strategic Problem Solving
- Mission-Focused Innovation
- Cross-Functional Collaboration, * 17 years with a Bachelor's degree in Computer Science, Engineering, Data Science, Advanced Mathematics, or related technical field, or 10 years with a Master's Degree in Computer Science, Engineering, Data Science, Advanced Mathematics, or related technical field, or 7 years with a Ph.D in Computer Science, Engineering, Data Science, Advanced Mathematics, or related technical field
- Strong proficiency with Python and AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras
- Experience with cloud platforms including AWS, Azure, or Google Cloud Platform
- Experience with MLOps, CI/CD pipelines, Docker, Kubernetes, and distributed systems
- Strong understanding of data pipelines, model lifecycle management, and scalable AI architectures
- Experience operating within Agile or DevSecOps environments
- Excellent communication and stakeholder engagement skills
- Active/current TS/SCI security clearance with a current polygraph is required.
Preferred Qualifications
- Experience supporting Intelligence Community (IC), DoD, or federal government programs
- Experience with Large Language Models (LLMs), Generative AI, RAG architectures, and vector databases
- Familiarity with AI governance, explainable AI (XAI), and responsible AI practices
- Experience with Spark, Kafka, Hadoop, or GPU-enabled distributed computing platforms