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Ensemble Health Partners
Lead Machine Learning EngineerEnsemble Health Partners • Hyderabad / Secunderabad, Telangana, India
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Lead Machine Learning Engineer

Lead Machine Learning Engineer

Ensemble Health Partners • Hyderabad / Secunderabad, Telangana, India
30+ days ago
Job description

Job Title

Lead – Analytics (AI Innovation)

Experience: 8-12 Years

Location: Remote – India Employment Type

Full-Time, Regular

Company Overview:

Ensemble Health Partners India is at the forefront of innovation in the Revenue Cycle Management (RCM) space, leveraging modern technology to drive meaningful, real world impact. Our future ready platforms bring together AI driven analytics, intelligent data ingestion, workflow automation, and business intelligence built on a scalable, cloud native architecture. Our AI powered solutions are actively running in production, continuously optimizing processes and delivering data driven insights at scale. With the second largest market share in the U.S. RCM industry, a global workforce of 15,000+ professionals, and 12 technology patents, we deliver results through strong teams, proven processes, and flexible, modern technologies. As part of our continued growth, we have launched our Global Capability Center (GCC) in Hyderabad designed to serve as a strategic extension of our global operations. The GCC brings together technology, analytics, and RCM expertise to build scalable solutions, accelerate innovation, and support our long term vision of transforming healthcare operations. At Ensemble Health Partners India, we foster a culture of growth, collaboration, and innovation where your expertise is valued, your ideas are heard, and your work makes a measurable impact.

Position Overview:

Job Title

Lead – Analytics (AI Innovation)

Location : Remote – India Employment Type

Full-Time, Regular

About the Role

Ensemble Health Partners is looking for a highly experienced Lead – Analytics to join our AI Innovation group. This is a senior individual contributor and technical leadership role, focused on building production-grade AI and ML systems that transform healthcare revenue cycle management (RCM).

In this role, you will lead engineering excellence across analytics and ML platforms, drive agentic AI development, execute radical simplification of complex ML pipelines, and systematically reduce technical debt. You will work closely with architecture, product, compliance, and engineering teams to deliver scalable, secure, and high-impact AI solutions.

This role is ideal for someone who combines deep hands-on technical expertise with strong influence, mentorship, and a passion for clean, maintainable, and high-quality engineering.

Key Responsibilities

1. Agentic AI Development

  • Design and implement agentic AI architectures that autonomously execute complex, multi-step RCM workflows
  • Build decision-making systems with strong guardrails, observability, and control mechanisms
  • Integrate autonomous AI agents with enterprise data platforms and revenue cycle systems
  • Evaluate and implement LLM-based and multi-agent frameworks for orchestration
  • Establish production-grade monitoring, logging, and incident response for AI agents
  • Partner with governance and compliance teams to ensure responsible AI deployment

2. Radical Simplification & Execution

  • Lead large-scale model consolidation initiatives, reducing client-specific ML models into generalized, reusable architectures
  • Simplify ML pipelines and reduce operational complexity across the analytics platform
  • Drive migration from self-managed Airflow to managed orchestration solutions
  • Identify and eliminate redundant systems, code, and processes to improve scalability and reliability
  • Document and evangelize simplification patterns across the organization

3. Code Craftsmanship & Engineering Excellence

  • Own and lead rigorous code review practices with a focus on quality, security, and maintainability
  • Create and maintain exemplar code libraries showcasing best practices and performance optimization
  • Define, implement, and enforce coding standards, design patterns, and Clean Architecture principles
  • Drive adoption of automated testing, CI/CD pipelines, and quality tooling
  • Champion security, Explainable AI (XAI), and responsible engineering as core principles
  • Mentor and upskill engineers through workshops, demos, and hands-on code reviews

4. Technical Debt Reduction

  • Conduct detailed technical debt assessments using static analysis and quality metrics
  • Prioritize and execute debt reduction initiatives aligned with business impact
  • Prevent future debt through strong engineering discipline and design reviews
  • Track and report technical debt metrics to leadership on a regular cadence

5. Cross-Functional Collaboration

  • Work closely with Architecture Leads to ensure alignment with Clean Architecture standards
  • Partner with Product, Compliance, and Security teams to deliver compliant AI solutions
  • Translate complex technical work into clear progress updates for business stakeholders
  • Lead cross-team knowledge sharing and technical communities of practice

Required Qualifications

  • 8+ years of overall software engineering experience
  • 5+ years in analytics, data science, or ML engineering roles
  • 2+ years in a senior IC or technical lead role
  • Expert-level Python development with strong focus on production-quality code
  • Proven experience designing, deploying, and operating ML systems in production
  • Strong background in code reviews, quality standards, and engineering best practices
  • Hands-on experience with ML pipelines, ETL workflows, and data platforms

Preferred Qualifications

  • Experience in healthcare revenue cycle management (RCM)
  • Exposure to agentic AI frameworks (e.g., LangGraph, AutoGen, CrewAI, Semantic Kernel)
  • Experience with cloud-based ML platforms (Azure ML, Databricks, Azure Data Factory, or similar)
  • Strong understanding of Clean Architecture and system design (C4 or equivalent)
  • Experience with model generalization techniques (ensembles, transfer learning, multi-task learning)
  • Familiarity with AI governance and compliance frameworks (NIST AI RMF, ISO 42001, HITRUST)
  • Experience quantifying and remediating technical debt using static analysis tools

What You'll Gain

  • Opportunity to build next-generation AI systems in healthcare
  • High ownership and autonomy in a senior technical leadership role
  • Strong visibility with senior and executive leadership
  • Access to learning platforms, certifications, and professional development budgets
  • Clear growth path toward senior technical and architectural leadership roles

Why Join US

• Work on real-world healthcare and technology challenges, powered by emerging technologies and a strong innovation mindset.

• Be part of a fast-growing, people-first organization where your work creates measurable impact.

• Grow continuously with structured learning, certifications, and industry-recognized development programs.

• Collaborate with high caliber teams that value ownership, trust, and accountability.

• Grow alongside an organization that's scaling with purpose and clarity. Be part of a fast scaling Global Capability Center with meaningful global responsibility.

Benefits:

Comprehensive health insurance coverage for associate, kids (2) and parents supporting physical and financial wellbeing beyond the workplace.

Accidental insurance coverage for the associate that adds an extra layer of security.

Professional development programs with reimbursement support to help you upskill and grow with confidence.

• A workplace that is fully compliant with labor laws, including maternity and paternity benefits.

• Thoughtful experiences like welcome kits, company swag, and work anniversary gifts that recognize your journey with us.

• Benefits designed to support you at different stages of life and career, not just on day one.

Please share your resume directly on [HIDDEN TEXT]


Skills Required
Data Science, Analytics, Python
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Lead Machine Learning Engineer • Hyderabad / Secunderabad, Telangana, India

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