Director of Machine Learning Engineering

THE POSITION
Our roster has an opening with your name on it

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.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN
Everyone on our team has a part to play

Strategic Leadership

• 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

Team Leadership

• 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

ML Engineering at Scale

• 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

Cross-Functional Collaboration

• 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

Operational Excellence

• 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

THE STATS
What we're looking for in our next teammate

• 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, Tensor Flow/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

Preferred Skills

• Experience…