ResponsibilitiesPosition Overview
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 roleserves as thetechnical 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 thebusiness acumennecessary 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 6 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
#MDFSP
Qualifications
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
Required Qualifications
- 17 years with a Bachelors 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
Target Salary Range$229,000 - $366,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individuals experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
