Lead Machine Learning Engineer, Platform

DraftKings • Boston, MA

12h

About The Position

At DraftKings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It’s transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We’re not waiting for the future to arrive. We’re shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together. The Crown Is Yours As a Lead Machine Learning Engineer, you’ll shape the future of AI and machine learning at DraftKings by designing scalable infrastructure and tooling that empowers teams to deliver production-grade AI systems. You’ll be a hands-on technical leader, collaborating across engineering, data science, and product to set best practices, standardize workflows, and ensure reliability from model training to real-time inference. If you're excited by cutting-edge AI and want to drive platform innovation at scale, this is your opportunity to make a meaningful impact.

Requirements

• At least 5 years of experience building and scaling production-grade ML or data platforms.
• Deep expertise in cloud-based environments such as AWS and Databricks.
• Proven knowledge of MLOps methodologies, including CI/CD, containerization, orchestration, model deployment, model observability, and feature stores.
• Strong cross-functional communication and collaboration skills, with a demonstrated ability to align technical vision across multiple teams.
• A passion for mentoring and a drive to stay on the cutting edge of ML infrastructure and AI technologies.
• Bachelor’s or Master’s Degree in Computer Science, Engineering, Artificial Intelligence, or a related technical field.

Responsibilities

• Support platform and infrastructure tooling for AI and Data Science teams by managing infrastructure code and providing enablement support.
• Lead high-impact technical initiatives that evolve our ML infrastructure with a focus on scalability, observability, automation, and lifecycle management.
• Design and implement real-time streaming architectures to power real-time ML, AI, and analytics applications.
• Champion engineering and MLOps best practices, including containerization, CI/CD, monitoring, and testing frameworks.
• Define and advocate for robust frameworks and standards to build and operate ML systems at scale.
• Collaborate cross-functionally with teams including Data Science, Data Platform, and Cloud Platform to align on strategy, scope, and technical priorities.
• Mentor engineers, fostering a culture of technical excellence, innovation, and continuous learning.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees