Machine Learning Associate Advisor -HIH-Evernorth at Cigna Group – Hyderabad | Jobyssey

As a Machine Learning Associate Advisor, you will leverage your expertise in PySpark and MLlib to design and optimize scalable machine learning workflows on Databricks. You will also be responsible for building and maintaining scalable cloud infrastructure on AWS. You’ll work closely with data scientists and product teams to build robust AI/ML pipelines that support advanced analytics and generative AI applications.

Responsibilities

Lead and mentor a team of MLOps and AI/ML Engineers, setting technical direction and engineering standards for building, deploying, and operating machine learning systems at scale.
Apply advanced ML techniques including supervised, unsupervised, and deep learning using PySpark, MLlib, and PyTorch.
Design and leverage AWS services such as EKS, EC2, SageMaker, Lambda, and S3.
Automate cloud resource provisioning and configuration using Terraform and Infrastructure as Code (IaC) best practices.
Collaborate with cross-functional teams to translate business requirements into scalable ML solutions.
Integrate Generative AI models (e.g., GPT, Claude) for tasks such as summarization, text generation, and conversational AI.
Develop APIs for model serving using FastAPI, supporting synchronous, asynchronous, and streaming inference.
Utilize AWS services (S3, Lambda, SageMaker, EC2) for model deployment and orchestration.
Implement CI/CD pipelines for ML models using GitHub Actions or Jenkins.

Required Experience

8+ years of relevant experience
Strong proficiency in PySpark and distributed data processing.
Experience with Databricks and MLlib.
Proficiency in container orchestration (EKS/Kubernetes).
Solid understanding of CI/CD practices and DevOps tooling.
Familiarity with deep learning frameworks like PyTorch.
Solid understanding of cloud-based ML deployment (AWS preferred).
API development experience with FastAPI.

Desired Experience

Javascript / React UI/UX Experience

Required Education

Bachelors or Masters (Preferred) in statistics, computer science or equivalent field

About Evernorth Health Services

Evernorth Health Services, a division of The Cigna Group, creates pharmacy, care and benefit solutions to improve health and increase vitality. We relentlessly innovate to make the prediction, prevention and treatment of illness and disease more accessible to millions of people. Join us in driving growth and improving lives.

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Responsibilities

Lead and mentor a team of MLOps and AI/ML Engineers, setting technical direction and engineering standards for building, deploying, and operating machine learning systems at scale.

Apply advanced ML techniques including supervised, unsupervised, and deep learning using PySpark, MLlib, and PyTorch.

Design and leverage AWS services such as EKS, EC2, SageMaker, Lambda, and S3.

Automate cloud resource provisioning and configuration using Terraform and Infrastructure as Code (IaC) best practices.

Collaborate with cross-functional teams to translate business requirements into scalable ML solutions.

Integrate Generative AI models (e.g., GPT, Claude) for tasks such as summarization, text generation, and conversational AI.

Develop APIs for model serving using FastAPI, supporting synchronous, asynchronous, and streaming inference.

Utilize AWS services (S3, Lambda, SageMaker, EC2) for model deployment and orchestration.

Implement CI/CD pipelines for ML models using GitHub Actions or Jenkins.

Required Experience

8+ years of relevant experience

Strong proficiency in PySpark and distributed data processing.

Experience with Databricks and MLlib.

Proficiency in container orchestration (EKS/Kubernetes).

Solid understanding of CI/CD practices and DevOps tooling.

Familiarity with deep learning frameworks like PyTorch.

Solid understanding of cloud-based ML deployment (AWS preferred).

API development experience with FastAPI.

Desired Experience

Javascript / React UI/UX Experience

Required Education

Bachelors or Masters (Preferred) in statistics, computer science or equivalent field