Lead AI/ML Engineer

Accountabilities:

• • Lead technical evaluations of emerging AI and machine learning technologies through prototypes, proof-of-concepts, experimentation, and comparative assessments.
  • Analyze the benefits, limitations, tradeoffs, implementation considerations, and risks of emerging technologies and communicate findings to technical and business stakeholders.
  • Design, develop, test, and deploy production-ready AI/ML applications within AWS cloud environments.
  • Build, train, evaluate, and optimize machine learning models for enterprise and mission-critical use cases.
  • Support AI/ML application development across engineering, operations, security, and other cloud-native disciplines.
  • Drive adoption of modern AI technologies, engineering practices, and scalable approaches across enterprise environments.
  • Collaborate directly with federal clients and multidisciplinary engineering teams to understand requirements and deliver high-impact technical solutions.
  • Present technical findings, experiment results, architecture recommendations, and implementation strategies to clients, executive stakeholders, and internal leadership.
  • Provide technical leadership and mentorship to software and machine learning engineers, helping strengthen engineering capabilities and professional development.
  • Contribute across multiple projects, rapidly assessing new technologies and determining how they can be applied to solve real-world challenges.
  • Support the development and adoption of MLOps, CI/CD, containerization, DevSecOps, and secure software engineering practices where appropriate.

  Requirements

  • Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Information Systems, or a related technical discipline, or equivalent professional experience.
  • 7–10 years of professional experience in software engineering, cloud engineering, or a closely related technical field.
  • At least 3 years of experience deploying production enterprise applications in AWS environments.
  • At least 2 years of experience deploying production AI/ML applications within enterprise environments.
  • Strong Python programming skills and hands-on experience with machine learning frameworks such as TensorFlow or PyTorch.
  • Experience with AI/ML platforms and services such as Amazon Bedrock, SageMaker, Hugging Face, Weights & Biases, or comparable technologies.
  • Strong experience with data analysis and manipulation using pandas, as well as experiment visualization and presentation using tools such as matplotlib.
  • Strong analytical, problem-solving, and technical communication skills, with the ability to explain complex AI/ML concepts to both technical and executive audiences.
  • Ability to quickly learn emerging technologies and contribute effectively across multiple projects and technical domains.
  • Experience leading, managing, or mentoring engineering or ML teams is highly desirable.
  • Experience with LLMs, generative AI, retrieval-augmented generation (RAG), AI agents, MLOps, Docker, Kubernetes, CI/CD, DevSecOps, or secure software development is a strong advantage.
  • Experience supporting federal, regulated, or mission-critical environments is beneficial.
  • Applicants must be U.S. Citizens and able to obtain a Public Trust clearance.

  Benefits

  • Annual salary range of $180,000–$230,000 USD, with final compensation based on experience, education, skills, and other relevant factors.
  • Eligibility for an annual discretionary bonus and performance-based incentive opportunities.
  • Remote work environment, with hybrid arrangements specified where applicable.
  • Medical, dental, and vision insurance.
  • Life insurance and short- and long-term disability coverage.
  • Employee Assistance Program.
  • 401(k) plan with 4% company matching.
  • Liberal paid time off and vacation policy.
  • Generous annual continuing education support.
  • Annual wellness budget.
  • Employee referral and performance-based bonus programs.
  • Opportunity to work on meaningful AI/ML initiatives supporting high-impact federal missions.
  • Collaborative environment with opportunities for technical leadership, mentorship, and professional growth.