Machine Learning Engineer

Norstella; Indiana; Hybrid; USD 100,000 - 150,000; Full time

Benefits offered by this job

Health Insurance

Provident Fund

Reimbursement of Certification

Gratuity

24x7 Health Desk

Job summary

Norstella is searching for a Machine Learning Engineer to develop ML and LLM systems, focusing on market access intelligence. This remote position requires strong production ML engineering skills and a deep understanding of LLMs.

The role demands collaboration with cross-functional teams to translate coverage and access requirements into operational models. Candidates should have 3+ years in machine learning engineering and hands-on experience with AWS services.

Qualifications

• 3+ years of experience in ML engineering with deployment focus.
• Hands-on experience with generative AI and LLMs.
• Strong programming skills in Python.
• Understanding of US market access data.

Responsibilities

• Design and deploy ML models interpreting payer coverage data.
• Tune LLMs for market access tasks with a specific focus.
• Collaborate with SMEs to refine fine-tuning datasets.
• Implement MLOps best practices to ensure data quality.
• Build secure AWS SageMaker endpoints.

Skills

Machine learning engineering

LLM systems

Python programming

Data analysis

AWS services

MLOps practices

Problem-solving

Communication skills

Education

Bachelor’s or graduate degree in computer science, STEM, or life sciences

Tools

scikit-learn

pandas

scipy

flask

FastAPI

Job description

Machine Learning Engineer

Company: Norstella

Location: Remote, India

Date Posted: Jul 22, 2026

Employment Type: Full Time

Job ID: R-2036

About Norstella

At Norstella, our mission is simple: to help our clients bring life-saving therapies to market quicker—and help patients in need.

Founded in 2022, but with history going back to 1939, Norstella unites best-in‑class brands to help clients navigate the complexities at each step of the drug development life cycle —and get the right treatments to the right patients at the right time.

Each organization (Citeline, Evaluate, MMIT, Panalgo, The Dedham Group) delivers must‑have answers for critical strategic and commercial decision‑making. Together, via our market‑leading brands, we help our clients:

• Citeline – accelerate the drug development cycle
• Evaluate – bring the right drugs to market
• MMIT – identify barrier to patient access
• Panalgo – turn data into insight faster
• The Dedham Group – think strategically for specialty therapeutics

By combining the efforts of each organization under Norstella, we can offer an even wider breadth of expertise, cutting‑edge data solutions and expert advisory services alongside advanced technologies such as real‑world data, machine learning and predictive analytics.

As one of the largest global pharma intelligence solution providers, Norstella has a footprint across the globe with teams of experts delivering world class solutions in the USA, UK, The Netherlands, Japan, China and India.

Job Description

We are seeking an ML Engineer to build and ship the machine learning and LLM systems behind MMIT’s market access intelligence. MMIT, a Norstella company, is the market access arm of the group—helping life sciences clients understand and improve how their therapies are covered, from formulary status and prior authorization to covered lives and benefit design.

In this role you will pair strong production ML engineering with real market access fluency and, above all, deep hands‑on command of large language models (LLMs)—how they work and how to tune them. You will turn US payer and coverage data into predictive analytics, plain‑language answers, and agentic workflows that commercial and market access teams can act on.

The role sits at the intersection of applied AI engineering and market access domain expertise. You will work across cross‑functional teams of data scientists, machine learning engineers, data engineers, and market access subject matter experts (SMEs)—translating coverage and access requirements into models and agents, adapting LLMs to internalize the desired end‑to‑end behavior, and operationalizing them reliably and compliantly in production.

Responsibilities

• Design, build, and deploy machine learning and LLM‑based models—including systems that interpret payer coverage, formulary status, and prior authorization / step therapy requirements—into production, collaborating closely with data engineers and data scientists.
• Adapt and tune LLMs for market access tasks—including fine‑tuning, prompt and instruction design, retrieval augmentation, and parameter/behavior optimization, so models internalize the desired end‑to‑end behavior across the target task surface area, edge cases, and known failure modes.
• Design, build, and continuously refine fine‑tuning datasets consisting of input/output pairs that demonstrate gold‑standard behavior, partnering with market access SMEs to shape schema, vocabulary, and the definition of “what good output looks like.”
• Run iterative model experiments: diagnose where a model is failing, design targeted data or prompt changes to close those gaps and measure the impact of each change with human‑in‑the‑loop SMEs.
• Build and operationalize evaluation harnesses; enable SME graders to run eval rounds and translate their feedback into concrete model, dataset, and tool‑call‑layer improvements.
• Design and build agentic workflows on domain‑grounded language models, including surfacing authoritative coverage and access data to LLMs via MCP (Model Context Protocol) servers and consuming them into agentic pipelines.
• Create secure AWS SageMaker endpoints and Lambdas, and define request/response formats and the appropriate AWS service per use case, to operationalize models as scalable services.
• Develop and maintain secure, robust, and scalable data pipelines for market access and coverage data feeding training, fine‑tuning, and inference workloads.
• Implement MLOps best practices—including data and model drift checks, monitoring, and troubleshooting—to ensure data quality, accuracy, and reliability; integrate these checks and stages (e.g., automated deployment following successful re‑training or re‑tuning) within the CI/CD pipeline.
• Maintain provenance, licensing, and compliance documentation for datasets and models, ensuring training data and workflows meet GxP, regulatory, and intellectual property standards expected in life sciences and market access settings.
• Conduct proofs of concept for novel market access capabilities and contribute to Norstella’s knowledge base and taxonomy work.

Qualifications

• Bachelor’s or graduate degree in computer science, STEM, life sciences, or equivalent professional experience.
• At least 3 years of professional experience in machine learning engineering, with a focus on deploying secure and robust models in production.
• Hands‑on experience with Generative AI, especially LLMs and agents, throughout the entire software development lifecycle (SDLC)—including a strong working understanding of how LLMs behave and how to tune them (fine‑tuning, prompt/instruction design, and evaluation).
• Experience creating MCPs and consuming them into agentic workflows.
• Strong programming skills in Python, with experience in libraries such as scikit‑learn, pandas, scipy, click, and flask and/or FastAPI.
• Good to have – Experience working with Market Access data and/or understanding of therapeutic areas from a clinical standpoint.
• Experience with the AWS ecosystem, specifically with services like SageMaker and Lambda.
• Experience working with US market access data—such as payer coverage, formulary status, prior authorization / step therapy criteria, covered lives, and benefit design—and a good understanding of the drug and procedure codes used in access analytics (NDCs, J‑codes, HCPCS, ICD‑10).
• Experience working with and statistically analyzing large and complex data sets, including data cleaning and preprocessing.
• Good understanding of the software development lifecycle and practices, including Git and version control, code reviews, and functional, unit, and integration testing.
• Excellent problem‑solving skills and the ability to work independently.
• Excellent communication skills, especially between technical and non‑technical teams.

Shift timing - 4PM to 1AM IST

Good to have skills

• Knowledge of non‑market‑access life sciences data assets, such as EMR, medical and pharmacy claims, and clinical trials data.
• Developing, evaluating, deploying, and monitoring algorithms and models from proof‑of‑concept, experimental stages through to production, in a reproducible, auditable, GxP‑compliant manner.
• AWS services beyond SageMaker and Lambda, such as S3, EC2, ECS, ECR, API Gateway, DynamoDB, and Bedrock.
• CI/CD processes, especially as applied to ML operations (MLOps), preferably with Azure DevOps.
• Advanced machine learning techniques (neural networks, ensemble learning, reinforcement learning, etc.) and the ability to implement them in Python.
• Docker or other containerization technologies.
• Fast‑paced, novel development cycles.

Our Guiding Principles for success at Norstella

• 01: Bold, Passionate, Mission-First
• 02: Integrity, Truth, Reality
• 03: Kindness, Empathy, Grace
• 04: Resilience, Mettle, Perseverance
• 05: Humility, Gratitude, Learning

Benefits

• Health Insurance
• Provident Fund
• Reimbursement of Certification Expenses
• Gratuity
• 24x7 Health Desk

  Norstella is an equal opportunity employer. All job applicants will receive equal treatment regardless of race, creed, color, religion, alienage or national origin, ancestry, citizenship status, age, physical or mental disability or handicap, medical condition, sex (including pregnancy and pregnancy‑related conditions), marital or domestic partner status, military or veteran status, gender, gender identity or expression, sexual orientation, genetic information, reproductive health decision making, or any other protected characteristic as established by federal, state, or local law.

  Sometimes the best opportunities are hidden by self‑doubt. We disqualify ourselves before we have the opportunity to be considered. Regardless of where you came from, how you identify, or the path that led you here- you are welcome. If you read this job description and feel passion and excitement, we’re just as excited about you.

  Norstella is an equal opportunity employer. All job applicants will receive equal treatment regardless of race, creed, color, religion, alienage or national origin, ancestry, citizenship status, age, physical or mental disability or handicap, medical condition, sex (including pregnancy and pregnancy‑related conditions), marital or domestic partner status, military or veteran status, gender, gender identity or expression, sexual orientation, genetic information, reproductive health decision making, or any other protected characteristic as established by federal, state, or local law.