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Raftvia Greenhouse

Lead AI/ML Engineer

McLean, VAPosted 2w ago
ML EngineerLeadFull-time

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About the Role

This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

About the role: 

We are seeking a Lead AI/ML Engineer to drive the design, development, and deployment of machine learning and AI systems that operate in mission-critical environments. You will lead the end-to-end lifecycle of AI solutions, from data ingestion and model development to production deployment, while guiding a cross-functional team across engineering, data, and product.

This role sits at the intersection of advanced AI capabilities and real-world operational impact. You will work closely with customers and internal stakeholders to deliver scalable, secure, and high-performance systems across cloud and edge environments.

What You’ll Do

  • Lead the architecture and development of AI/ML systems integrated into production-grade data platforms
  • Design and implement scalable ML pipelines including training, inference, and evaluation in distributed environments
  • Drive adoption of modern AI approaches including LLMs, retrieval augmented generation, and agentic workflows
  • Design, train, fine-tune, and deploy purpose-built Small Language Models (SLMs) optimized for domain-specific tasks, including quantization, distillation, and optimization techniques that enable low-latency inference in resource-constrained, edge, and air-gapped environments
  • Partner with Data Engineers and DevSecOps to operationalize models in secure, containerized environments including Kubernetes and CI/CD pipelines
  • Translate mission needs into technical solutions while working directly with customers and stakeholders
  • Mentor and guide engineers while setting technical direction and best practices for AI/ML development
  • Ensure models are reliable, observable, and performant in real-world operational conditions
  • Own the enterprise-wide AI/ML strategy and multi-year technical roadmap, aligning research, engineering, and product investments with mission outcomes and commercial objectives
  • Build, scale, and lead a multi-team AI/ML organization, including hiring, performance management, and developing senior technical leaders across applied research, ML engineering, and MLOps
  • Establish and steward the technical vision for agentic systems, foundation models, and emerging AI paradigms, identifying strategic bets and guiding applied research investments that create long-term competitive advantage

What we are looking for: 

  • Advanced degree (Master’s or PhD) in Computer Science, Artificial Intelligence, or a related STEM field
  • 8+ years of experience in AI/ML engineering, software engineering, or related field
  • Strong background in building and deploying machine learning models in production environments
  • Experience designing and maintaining ML pipelines and platforms including training, inference, and monitoring
  • Proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, or Scikit-learn
  • Strong software engineering fundamentals including APIs, microservices, testing, and version control
  • Experience working in cloud-native environments such as AWS, Kubernetes, and containerization
  • Ability to lead technical initiatives and collaborate across interdisciplinary teams
  • Track record of setting multi-year technical strategy and delivering AI/ML capabilities that directly drove revenue growth, customer acquisition, or measurable mission impact
  • Experience establishing AI governance, model risk management, and responsible AI practices at an enterprise scale

Highly preferred:

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