Principal Machine Learning Engineer
- Compensation
- Not disclosed
- Location
- Remote CW Site - USA - Flexible United States
- Work setup
- Remote
- Seniority
- Principal
- Employment
- Not specified
- Experience
- 6+ years
- Category
- Ml / AI
- Posted
Skills
Nice to have
- Experience establishing an ML or AI platform capability in an organisation that did not previously have one.
Full description
Job Title
Principal Machine Learning Engineer
Job Description Summary
We are seeking a Principal ML Engineer to build and maintain artificial intelligence and machine learning systems for our business. This role combines deep technical execution with broad influence: tackling the most complex machine learning problems, designing and implementing data architectures/models, MLOps and LLMOps, and monitoring and optimization as key software, while raising the bar for engineering excellence across the Data Organization.
Reporting to the Senior Director, Data Science & AI, the Principal ML Engineer is expected to move fluidly across project/product teams — embedding in projects for days or months at a time to unblock, accelerate, and uplift delivery. They will mentor other engineers at every level, push standards for technical excellence, and help establish the ML engineering, and architectural principles that guide our work. The primary platform is Databricks and the Azure cloud ecosystem, with the expectation of evaluating and adopting additional data technologies as the platform evolves.
Job Description
Role Summary
We are seeking a Principal ML Engineer to build and maintain artificial intelligence and machine learning systems for ourbusiness. This role combines deep technical execution with broad influence: tackling the most complex machine learning problems, designing and implementing data architectures/models, MLOps and LLMOps, and monitoring and optimization as key software, while raising the bar for engineering excellence across the Data Organization.
Reporting to the Senior Director, Data Science & AI, the Principal ML Engineer is expected to move fluidly across project/product teams — embedding in projects for days or months at a time to unblock, accelerate, and uplift delivery. They will mentor other engineers at every level, push standards for technical excellence, and help establish the ML engineering, and architectural principles that guide our work. The primary platform is Databricks and the Azure cloud ecosystem, with the expectation of evaluating and adopting additional data technologies as the platform evolves.
Key Responsibilities
AI/ML Model Development
- Demonstrable experience shaping the end-to-end architecture, development, and deployment of AI, including machine learning, GenAI, and Agentic models that are tailored to business use cases.
- Design and develop agentic AI systems — including multi-agent orchestration, tool-use, evaluation, and autonomous task-execution pipelines — to automate complex enterprise workflows.
- Enforce model development standards encompassing data preprocessing, feature engineering, model selection, hyperparameter tuning, evaluation, and documentation.