Principal ML Engineer

The role

You will serve as a senior technical leader for the Predictive Intelligence engineering team. You will participate in architecture and technical strategy for predictive intelligence services and build ML platforms, forecasting engines, and data processing services.

What you will do

• Participate in the overall architecture and technical strategy for predictive intelligence services.
• Drive a unified approach across intelligence services to reduce duplication.
• Provide hands-on design and implementation leadership for major features and platform initiatives.
• Write and review critical-path code.
• Establish and evangelize engineering best practices for scalability, fault tolerance, observability, and operational excellence.
• Mentor senior engineers.
• Partner with data scientists to shorten the path from research to production.
• Partner with Product, Data Science, and Platform leadership to shape the technical roadmap.
• Represent the AI engineering organization in technical conversations and architectural reviews.

Required qualifications

• Extensive commercial professional software engineering experience.
• Strong background within a Principal role owning systems at scale.
• Deep expertise in Python.
• Experience designing and operating high-availability, production ML services.
• Experience designing and operating data and analytics platforms built on technologies such as Snowflake, Iceberg, Trino, and Postgres.
• Production experience with Kubernetes.
• Experience with at least one major cloud provider (AWS, GCP, or Azure).
• Working familiarity across multi-cloud environments.
• Demonstrated experience with MLOps tooling and patterns, including model registries, experiment tracking, and CI/CD.
• Ability to lead technical strategy across multiple teams and services.
• Strong communicator.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

Nice to have

• Experience operating forecasting models in production, including gradient-boosted methods, neural networks, and constraint-based optimization solvers.
• Domain background in retail, supply chain, demand planning, or financial planning.
• Experience leading post-acquisition platform integration or cross-organization architectural alignment.
• Open-source contributions to ML infrastructure, data processing, or related ecosystems.
• Advanced degree in Computer Science, Machine Learning, Statistics, or a related field.

About the company

Anaplan is a team of innovators focused on optimizing business decision-making through an AI-infused scenario planning and analysis platform. Their customers include global companies like Coca-Cola, LinkedIn, Adobe, LVMH, and Bayer.