Bespoke Technologies, Inc.
On-siteChantilly, Virginia, United States
Job Summary
Lead, mentor, and manage a team of ML modeling developers and MLOps engineers dedicated to productionizing machine learning. Define and execute the technical strategy for the MaaS platform, overseeing the design, development, and deployment of a diverse portfolio of models to solve complex challenges. Establish robust MLOps practices to ensure automated, reliable, and scalable CI/CD pipelines, while architecting a service layer that exposes models via secure, scalable APIs. Collaborate with data scientists and stakeholders to identify use cases and implement governance, security, and ethical AI standards across the entire model lifecycle. Manage project timelines, resource allocation, and stakeholder communication for all MaaS initiatives. This strategic leadership role defines the vision for centralized AI/ML model access across the enterprise.
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
Desired 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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