Senior Principal Machine Learning Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Principal Machine Learning Engineer based in the United States.

The Senior Principal Machine Learning Engineer will lead the design and delivery of advanced machine learning and AI systems that transform complex healthcare data into measurable business and operational outcomes.

This role combines applied research, large-scale production engineering, and technical leadership to solve high-impact challenges involving claims, clinical data, and risk management.

The position will define AI/ML strategy, build scalable solutions, and establish engineering practices that improve accuracy, auditability, and decision-making.

Working across engineering, product, clinical, and analytics teams, this leader will translate ambiguous challenges into reliable, production-ready systems.

The ideal candidate brings deep expertise in machine learning, experimentation, and AI architecture while influencing technical direction across the organization.

This is an opportunity to shape next-generation AI capabilities in a highly regulated environment where precision, innovation, and measurable impact are critical.

Accountabilities

The Senior Principal Machine Learning Engineer will provide technical leadership across the development of AI-powered products, driving the architecture, implementation, and continuous improvement of scalable machine learning systems. This role requires a combination of hands-on engineering expertise, strategic thinking, and the ability to influence teams across the organization.

• 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, ensuring accuracy, reliability, and auditability.
• Create data flywheel strategies by transforming expert feedback and review decisions into high-quality training data and model improvements.
• Explore and develop patient-level digital twin approaches to unify clinical data processing and improve healthcare insights.
• Lead ranking, prioritization, and classification systems that identify high-value opportunities for review and improve operational efficiency.
• Establish reusable ML platform patterns, including shared context stores, evaluation frameworks, and feature pipelines.
• Partner with engineering, product, clinical, and analytics teams to define objectives, success metrics, and production strategies.
• Mentor senior engineers and elevate standards around machine learning engineering, experimentation, and system design.
• Influence enterprise-wide AI/ML strategy and contribute thought leadership within the broader industry.

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• Drive technical excellence through strong documentation, rigorous experimentation, and scalable engineering practices.
  
  

Requirements

The ideal candidate is a highly experienced machine learning leader with a proven ability to build production ML systems at scale and drive technical strategy across complex organizations. They combine deep technical expertise with strong communication skills and experience operating in high-impact, regulated environments.

• PhD in a quantitative discipline such as Computer Science, Engineering, Statistics, Operations Research, or a related field covering advanced statistics, machine learning, and AI.
• 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, large-scale classification, or AI model optimization.
• Proven experience leading end-to-end ML initiatives from problem definition through production deployment and measurable business impact.
• Strong experimentation background, including A/B testing, causal inference, metric development, and opportunity analysis.
• Advanced proficiency in Python, PyTorch, SQL at scale (such as Presto, Trino, or Spark), and distributed data pipeline technologies such as Airflow.
• Demonstrated ability to align engineering, product, analytics, and business teams around shared technical goals.
• Experience building LLM evaluation pipelines, supervised fine-tuning workflows, embedding models, or reranking systems is highly valued.
• Familiarity with healthcare data, including claims, electronic health records, clinical coding systems, or healthcare analytics is preferred.
• Experience designing ML systems for regulated, auditable, or high-stakes environments such as healthcare, finance, or fraud detection.
• Knowledge of secure data practices and compliance frameworks for sensitive information, including HIPAA environments.
• Strong problem-solving abilities with the ability to independently analyze data, make decisions, and communicate complex technical concepts.
• Ability to provide a secure remote workspace with reliable high-speed internet connectivity.
  
  

Benefits

• Competitive base salary range of $250,000-$280,000 per year, with final compensation determined by experience, education, skills, certifications, and business needs.
• Eligibility for discretionary bonus opportunities.
• Comprehensive benefits package including medical, dental, vision, disability, and life insurance coverage.
• 401(k) savings plan to support long-term financial planning.
• Paid family leave and supportive benefits for personal and family needs.
• Paid holidays and 17-27 days of paid time off (PTO) depending on level and tenure.
• Fully remote work environment with virtual interview process.
• Opportunity to lead impactful AI initiatives and shape machine learning systems used in a high-value industry.
• Exposure to advanced AI technologies and complex real-world data challenges.
• Collaborative environment with opportunities for technical leadership and professional growth.
  
  

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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