Senior Principal Machine Learning Engineer
New
Based in the United StatesFull-TimePrincipal
Salary$250,000–$280,000 per year
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Job Details
- Experience
- 12+ years of industry experience
- Required Skills
- PythonSQLMachine LearningPyTorchAirflowA/B testingLLMHIPAA
Requirements
- PhD in a quantitative discipline such as Computer Science, Engineering, Statistics, or Operations Research.
- 12+ years of industry experience building and deploying production machine learning systems at scale.
- Deep expertise in two or more areas including LLM evaluation, retrieval-augmented generation (RAG), ranking systems, or large-scale classification.
- Proven experience leading end-to-end ML initiatives from problem definition through production.
- Strong experimentation background including A/B testing, causal inference, and metric development.
- Advanced proficiency in Python, PyTorch, SQL at scale, and distributed data pipeline technologies like Airflow.
- Demonstrated ability to align engineering, product, and business teams.
- Knowledge of secure data practices and compliance frameworks including HIPAA.
- Experience designing ML systems for regulated or high-stakes environments such as healthcare or finance.
- Ability to provide a secure remote workspace with reliable high-speed internet connectivity.
Responsibilities
- Define end-to-end system architecture for AI and LLM-powered solutions processing claims, medical records, and clinical documentation.
- Design, build, and maintain scalable machine learning systems that improve payment accuracy, risk adjustment, and quality outcomes.
- Develop advanced evaluation frameworks, including LLM-as-a-Judge, offline metrics, and online experimentation.
- Create data flywheel strategies by transforming expert feedback into high-quality training data.
- Lead ranking, prioritization, and classification systems that improve operational efficiency.
- Establish reusable ML platform patterns, including shared context stores and feature pipelines.
- Partner with engineering, product, clinical, and analytics teams to define objectives and success metrics.
- Mentor senior engineers and elevate standards around machine learning engineering and system design.
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