Principal Machine Learning Engineer

Role overview Provide senior technical leadership for the design, delivery, and operation of machine learning and AI systems. The work spans complex model development, data architecture, MLOps and LLMOps, production monitoring, and engineering standards. You’ll move between teams to unblock projects, improve delivery, and mentor engineers, while helping shape the organization’s ML architecture and practices.

Responsibilities - Design and deliver AI systems for business needs, including machine learning, generative AI, and agentic models. - Build agent workflows that can coordinate multiple agents, use tools, undergo evaluation, and automate complex tasks. - Set standards for data preparation, feature engineering, model selection, tuning, evaluation, and documentation. - Work with data engineering teams on reliable pipelines for training and inference. - Establish MLOps and LLMOps practices for development, evaluation, deployment, versioning, experiment tracking, and model registries. - Monitor production models for performance changes, drift, and bias; support alerting and retraining processes. - Help establish governance for model risk, fairness, explainability, privacy, and security, with human oversight and accountability. - Mentor engineers and raise technical standards across teams.

Requirements - At least 10 years building software or machine learning systems, including six or more years shipping and operating production ML systems. - Experience making architectural decisions for a production ML or data platform. - A record of establishing technical standards and leading through influence. - Strong hands-on Python and SQL skills.

Nice to have Experience creating an ML or AI platform capability; working across teams, regions, and time zones; using CI/CD or infrastructure-as-code tools; and familiarity with data governance, model serving, feature stores, retrieval pipelines, or tool-integration standards. Experience in a data-complex domain is also valued.

Benefits and work setup The primary platform is Databricks on Azure, with room to evaluate additional data technologies. The listed compensation range is $178,500–$210,000. Eligible employees may enroll in health, dental, vision, savings, insurance, and time-away programs.