Data Scientist

Coforge; Auburn Hills (MI); On-site; USD 110,000 - 160,000; Full time

Job summary

Coforge is seeking an experienced Data Scientist in Auburn Hills, MI to design, develop, and deploy ML solutions on AWS. You will work with LLMs and agentic AI, building RAG workflows and surface model outputs through modern front-end interfaces.

The role requires strong coding in Python/Java and hands-on Docker/GPU experience. The candidate should have 8+ years of relevant experience, be comfortable with onsite work, and contribute to model governance, testing, and bias mitigation while

Qualifications

• Strong hands-on experience building and deploying ML solutions on AWS.
• Proven experience with LLMs, including OpenAI models/APIs, and current knowledge of leading AI/LLM model families.
• Hands-on experience building agentic AI systems (multi-agent orchestration, tool use, autonomous workflows).
• Experience building RAG systems, including semantic RAG (embeddings, vector databases, semantic retrieval).
• Deep understanding of data: exploration, quality, feature engineering, and its impact on model outcomes.
• Strong coding proficiency in Python and Java.
• Experience building front-end interactive applications (React, TypeScript, or Java-based UI) to surface model outputs to end users.
• Practical experience with Docker/containers and GPU compute for training/inference.
• Experience building and maintaining CI/CD pipelines for ML/AI workloads.
• Working knowledge of DevSecOps practices applied to ML pipelines.
• Experience providing operational support for production ML/AI systems, including monitoring and incident response.
• Experience implementing model governance and monitoring (drift detection, performance tracking, periodic retraining/tuning cycles).
• Demonstrated ability to design for human-in-the-loop / human-on-the-loop workflows for model oversight, retraining, and tuning.
• Demonstrated judgment in model/technique selection, including when to use AI/LLM approaches vs. traditional methods.
• Experience defining measurable testing/evaluation criteria for model performance and quality.
• Experience writing automated test cases, including using AI-assisted approaches to generate test coverage for model builds.
• Solid understanding of AI governance, legal, and security requirements, and experience embedding guardrails into model development.
• Familiarity with ML/AI frameworks (e.g., PyTorch, TensorFlow, Hugging Face, LangChain/LlamaIndex or similar agentic/RAG frameworks).

Responsibilities

• Develop and deploy ML solutions on AWS.
• Build and orchestrate agentic AI systems with multi-agent coordination.
• Design and implement RAG-based retrieval augmented workflows.
• Ensure data quality and feature engineering drive model performance.
• Develop front-end interfaces to surface model outputs to users.
• Implement packaging, containerization, and GPU-accelerated training/inference.
• Build and maintain CI/CD pipelines for ML workloads.
• Apply DevSecOps practices to ML pipelines and governance measures.
• Provide production support including monitoring and incident response.
• Define testing criteria and automate test coverage for models.

Skills

Data Scientist

AWS

ML Solutions

LLM

Python

Java

Docker/containers

CI/CD pipelines

DevSecOps

Model governance

Tools

PyTorch

TensorFlow

Hugging Face

LangChain/LlamaIndex

OpenAI API

Docker

CI/CD tools

Kubernetes

Job description

Skills: Data Scientist, AWS, ML Solutions, LLM, OpenAI, Agentic AI, RAG, Python, Java, Docker/containers, CI/CD pipelines, DevSecOps, and ML/AI frameworks (e.g., PyTorch, TensorFlow, Hugging Face, LangChain/ LlamaIndex or similar agentic/RAG frameworks)

Experience: 8+ Years

Location: Auburn Hills, MI

5 Days Onsite

We at Coforge are hiring a Data Scientist with the following skillset:

Required Skills & Qualifications (Mandatory)

• Strong hands-on experience building and deploying ML solutions on AWS.
• Proven experience with LLMs, including OpenAI models/APIs, and current knowledge of leading AI/LLM model families.
• Hands-on experience building agentic AI systems (multi-agent orchestration, tool use, autonomous workflows).
• Experience building RAG systems, including semantic RAG (embeddings, vector databases, semantic retrieval).
• Deep understanding of data: exploration, quality, feature engineering, and its impact on model outcomes.
• Strong coding proficiency in Python and Java.
• Experience building front-end interactive applications (React, TypeScript, or Java-based UI) to surface model outputs to end users.
• Practical experience with Docker/containers and GPU compute for training/inference.
• Experience building and maintaining CI/CD pipelines for ML/AI workloads.
• Working knowledge of DevSecOps practices applied to ML pipelines.
• Experience providing operational support for production ML/AI systems, including monitoring and incident response.
• Experience implementing model governance and monitoring (drift detection, performance tracking, periodic retraining/tuning cycles).
• Demonstrated ability to design for human-in-the-loop / human-on-the-loop workflows for model oversight, retraining, and tuning.
• Demonstrated judgment in model/technique selection, including when to use AI/LLM approaches vs. traditional methods.
• Experience defining measurable testing/evaluation criteria for model performance and quality.
• Experience writing automated test cases, including using AI-assisted approaches to generate test coverage for model builds.
• Solid understanding of AI governance, legal, and security requirements, and experience embedding guardrails into model development.
• Familiarity with ML/AI frameworks (e.g., PyTorch, TensorFlow, Hugging Face, LangChain/LlamaIndex or similar agentic/RAG frameworks).

Preferred Qualifications

• Working knowledge of GCP and Azure ML/AI services.
• Experience with responsible AI toolkits (bias/fairness testing, model explainability).
• Certifications in AWS ML/AI or relevant cloud platforms.