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Capital Technology Group

Lead AI/ML Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Information Systems, or a related technical field, or equivalent experience.
  • Seven to ten years of professional experience in software engineering or cloud engineering.
  • At least three years of experience deploying production enterprise applications in AWS.
  • At least two years of experience deploying production AI/ML applications in enterprise environments.
  • Strong proficiency in Python.
  • Experience with machine learning frameworks such as TensorFlow or PyTorch.
  • Experience with AI/ML platforms and services including Amazon Bedrock, SageMaker, Hugging Face, Weights & Biases, or similar technologies.
  • Strong data analysis and manipulation experience using pandas.
  • Experience visualizing and presenting experiment results using tools such as matplotlib.
  • Experience working within AWS cloud environments.
  • Ability to learn new technologies quickly and contribute across multiple projects.
  • Strong analytical and problem-solving skills.
  • Ability to present technical solutions to clients and executive stakeholders.
  • Applicants must be U.S. citizens.
  • Ability to obtain a Public Trust clearance.

Responsibilities

  • Lead technical evaluations of emerging AI/ML technologies through prototypes, proof of concepts, and experimentation.
  • Analyze and communicate the benefits, tradeoffs, and implementation risks of new technologies to technical and business stakeholders.
  • Design, develop, and deploy production-ready AI/ML applications within AWS cloud environments.
  • Support AI/ML application development across development, operations, and security disciplines in cloud-native environments.
  • Drive enterprise adoption of modern AI technologies and engineering best practices.
  • Build, train, evaluate, and optimize machine learning models for production use cases.
  • Collaborate directly with clients and cross-functional engineering teams to deliver mission-critical solutions.
  • Provide technical leadership by mentoring engineers and supporting the professional growth of junior team members.
  • Present technical findings, experiment results, and architectural recommendations to internal leadership and federal customers.

Desired Qualifications

  • Experience leading or managing engineering teams.
  • Experience mentoring software engineers or machine learning engineers.
  • Experience with large language models (LLMs), generative AI, Retrieval-Augmented Generation (RAG), or AI agents.
  • Experience deploying AI solutions using MLOps best practices.
  • Experience with containerization technologies such as Docker and Kubernetes.
  • Experience building CI/CD pipelines for AI/ML workloads.
  • Familiarity with DevSecOps and secure software development practices.
  • Experience supporting federal, highly regulated, or mission-critical environments.

About the Company

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