Engineer II, AI

Job Title: Engineer II, AI

Experience: 4- 6 Years

Location: Hyderabad and Bangalore

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 Summary:

Ensemble is a leader in revenue cycle management innovation, leveraging advanced analytics and machine learning to deliver high-impact solutions.

The Engineer II, AI role is focused on end-to-end machine learning (ML) development to optimize processes in healthcare revenue cycle management (RCM) operations. Candidates must have over 3 years of relevant experience to support data-driven decision-making in a dynamic environment. Please note, this is primarily an ML Engineer role, not a Data Scientist, or MLOps Role.

Job Responsibilities

• Contribute towards end-to-end ML development lifecycle, including data preparation, model building, deployment, and monitoring for revenue cycle applications.
• Build and optimize Gradient Boosting Trees models using LightGBM, and develop scikit-learn pipelines for predictive analytics.
• Implement Large Language Model (LLM) operations with OpenAI APIs, including summarization, prompt engineering, fine-tuning, and integration into operational workflows.
• Apply Explainable AI (XAI) techniques using libraries like SHAP and LIME to interpret model decisions and ensure transparency in high-stakes healthcare scenarios.
• Analyze complex datasets to identify patterns, develop deployable solutions, and collaborate on production-grade ML systems.

Required Skills

• Proficiency in Python and SQL for high-quality, production-ready code, with a public GitHub repository showcasing ML projects.
• MUST have actively programmed in python for 3 years
• SHOULD know SQL
• Expertise in ML libraries: scikit-learn, PySpark ML.
• Expertise in data manipulation libraries: pandas, Dask, Polars, PySpark.
• Expertise in data validation tools: Pydantic, Pandera.
• The right candidate should be able to pick up new technologies rapidly and contribute towards key initiatives.
• Hands-on experience with XAI libraries including but not limited to LIME, SHAP, BLEU, ROUGE etc.
• Strong knowledge of LLMs (OpenAI), including prompt engineering, tuning, and summarization tasks.
• Experience in healthcare or revenue cycle management is a plus.

Preferable Skills

• Exposure to healthcare analytics or revenue cycle management is advantageous but not mandatory. Such experience enhances the ability to apply ML solutions directly to domain-specific challenges in Ensemble’s operations. Candidates with this background can accelerate impact in revenue cycle optimization.
• Knowledge of Spark and experience in Databricks is a plus

Qualifications

• Undergraduate degree (B.E./B.Tech) in Engineering or Technology, or a graduate degree (M.Sc./M.S.) in Science, Mathematics, or Statistics (STEM).
• A first class, distinction, or top 10 percentile performance throughout the academic career is mandatory.
• Relevant experience exceeding 3 years is a key requirement alongside these academic credentials. People with a data/analytics background before the 3 years in ML Engineering with be preferred.