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AI/ML Engineer Manager
AI/ML Engineer ManagerBespoke Technologies • Remote, Remote, United States
AI / ML Engineer Manager

AI / ML Engineer Manager

Bespoke Technologies • Remote, Remote, United States
[job_card.30_days_ago]
[job_preview.job_type]
  • [job_card.full_time]
[job_card.job_description]

BT-160 – AI / ML Engineer Manager

Location : Chantilly / Herndon

  • MUST HAVE A TS / SCI CLEARANCE TO APPLY. Those without an active security clearance will not be considered.

Role Description :

As the Manager for the AI / ML Models as a Service (MaaS) team, you will lead a specialized group of developers and engineers dedicated to productionizing machine learning. Your mission is to build and manage a centralized platform that provides access to pre-trained and custom-built AI / ML models, simplifying their integration and accelerating the delivery of AI-powered capabilities across the enterprise . This is a strategic, hands-on leadership role where you will define the vision for our MaaS offerings and oversee the entire lifecycle of model development, deployment, and operations.

Responsibilities :

  • Lead, mentor, and manage a high-performing team of ML modeling developers and MLOps engineers.
  • Define and execute the technical strategy for the MaaS platform, including the frameworks for model training, versioning, deployment, and monitoring.
  • Oversee the design, development, and deployment of a diverse portfolio of machine learning models to solve complex challenges.
  • Establish and enforce robust MLOps practices to ensure automated, reliable, and scalable CI / CD pipelines for machine learning models.
  • Architect the service layer for the MaaS platform, ensuring models are exposed via secure, scalable, and well-documented APIs.
  • Collaborate with data scientists, data engineers, and stakeholders to identify use cases and translate requirements into production-ready models.
  • Implement governance, security, and ethical AI standards across the entire model lifecycle.
  • Manage project timelines, resource allocation, and stakeholder communication for all MaaS initiatives.

    • Required Qualifications :

  • 8+ years of experience in data science or machine learning engineering, with at least 3 years in a technical leadership or management role.
  • Deep expertise in developing and deploying ML models using common frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
  • Proven experience building and maintaining production ML systems in a cloud environment (AWS, Azure, GCP).
  • Strong understanding of MLOps principles and hands-on experience with relevant tools (e.g., MLflow, Kubeflow, AWS SageMaker, Azure ML).
  • Proficiency with containerization technologies (Docker, Kubernetes) and CI / CD tools.
  • Excellent programming skills in Python and familiarity with software engineering best practices.
  • Active Top Secret / SCI security clearance.

    • Preferred Qualifications :

  • Direct experience building a Model-as-a-Service or Machine-Learning-as-a-Service platform.
  • Experience with ML platforms like Databricks or AWS SageMaker AI.
  • Familiarity with Infrastructure-as-Code (IaC) tools like Terraform.
  • Experience working in a high-security environment.
  • Demonstrated success leading teams that deliver complex, data-driven software projects.
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