Director of Machine Learning Engineering

FanDuel • New York, NY

92d • $197,000 - $246,000

About The Position

We are seeking a Director of Machine Learning Engineering to lead a world-class team at the intersection of data science and machine learning engineering. This role is responsible for scaling the development, deployment, and operationalization of advanced machine learning systems across the organization—including personalization, forecasting, optimization, generosity, search and customer segmentation models. You will own the strategy and execution to deliver scalable, production-grade ML services that power key business decisions and customer experiences. This includes partnering closely with data science, engineering, and product teams to align on ML use cases, model performance, infrastructure needs, and long-term reusable architecture. If you’re a visionary leader with deep technical expertise in both data science and ML engineering and are passionate about building reusable ML services that deliver measurable business outcomes at scale—this is the role for you.

Requirements

• 8+ years of experience in data science, machine learning or data engineering, with 3+ years in a technical leadership or management role with a focus on machine learning.
• Proven experience building and managing robust, scalable machine learning pipelines and platforms.
• Expertise in modern ML and data technologies (e.g., Spark, Airflow, Kubeflow, Databricks, Kafka, TensorFlow/PyTorch, Feast, AWS ML services).
• Strong track record of partnering with data scientists to bring models into production and optimize performance.
• Experience working with cloud platforms such as AWS, GCP, or Azure.
• Excellent communication skills with the ability to influence technical and non-technical audiences.
• Demonstrated ability to lead high-performing teams and manage competing priorities in fast-paced environments.

Nice To Haves

• Experience supporting data science, or product development teams in a data-driven organization.
• Familiarity with ML product thinking and customer-centric data delivery.
• Understanding of machine learning workflows and advanced analytics pipelines.
• Background in DTC, eCommerce, or B2C digital environments.

Responsibilities

• Define and execute the strategy for machine learning services across the company, aligning with business goals and customer needs.
• Establish a vision and roadmap for scalable ML infrastructure, model lifecycle management, and ML-powered product capabilities.
• Partner with data science, data product, engineering, and executive leadership to identify and prioritize ML use cases that deliver clear business value.
• Hire, mentor, and grow a high-performing team of ML engineers.
• Create a culture of innovation, experimentation, and accountability—fostering best practices in model development, software engineering, and reproducibility.
• Provide technical and strategic mentorship to elevate the quality and impact of ML projects across the company.
• Lead the development and deployment of end-to-end ML systems—from experimentation and training to inference, monitoring, and continuous learning.
• Guide the team in building reusable model components, APIs, and pipelines for personalization, forecasting, fraud detection, and more.
• Ensure ML services are highly available, scalable, secure, and cost-efficient—leveraging modern MLOps practices and tooling.
• Serve as a bridge between data scientists, machine learning engineers, and platform engineers—ensuring models move seamlessly from prototype to production.
• Standardize model governance, performance monitoring, and retraining workflows in collaboration with stakeholders across teams.
• Translate complex ML capabilities into stakeholder-friendly language and value statements that resonate with business and product leaders.
• Improve development workflows to optimize productivity, observability, delivery speed, and quality.
• Drive efficiency and performance through effective resource planning and prioritization.
• Partner with data governance, privacy, and security teams to ensure regulatory compliance and best practices in data handling.

Benefits

• Array of health plans to choose from (some as low as $0 per paycheck) including programs for fertility and family planning, mental health support, and fitness benefits.
• Generous paid time off (PTO & sick leave).
• Annual bonus and long-term incentive opportunities (based on performance).
• 401k with up to a 5% match.
• Commuter benefits.
• Pet insurance.
• Paid personal time off and 14 paid company holidays.
• Paid sick time in accordance with all applicable state and federal laws.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Bachelor's degree