Senior AI ML Engineer

Solventum (3M Healthcare); Bengaluru; On-site; INR 450,000 - 700,000; Full time

Job summary

Solventum is seeking a Senior AI/ML Engineer / Data Scientist to design, develop, and deploy AI, ML, and Generative AI solutions across the supply chain. You will build scalable models, AI agents, and cloud-native applications using AWS and Azure to enable intelligent decision-making and automation.

You will collaborate with stakeholders and data teams to translate business requirements into reliable AI systems, with a focus on production-ready pipelines and enterprise data integration.

Qualifications

• Design, develop, and deploy scalable AI/ML solutions for complex supply chain challenges.
• Create AI agents and multi-agent workflows using modern frameworks to automate business processes.
• Build robust data ingestion and feature engineering pipelines for structured and unstructured data.

Responsibilities

• Design, develop, and deploy scalable Machine Learning models and AI solutions for supply chain.
• Design, build, test, and deploy AI Agents and multi-agent systems.
• Develop data ingestion, transformation, and feature engineering pipelines for enterprise data.
• Deploy and manage AI applications on AWS and Azure with MLOps.

Skills

AI/ML engineering

Generative AI

Cloud computing

Data pipelines

MLOps

Tools

Lang Graph

Lang Chain

Auto Gen

Crew AI

Job description

At Solventum, we improve lives by helping healthcare professionals do their best work. Join a team using innovation and insight to make a real impact on the future of healthcare. All roles listed are with Solventum, and we're committed to protecting your personal information-learn more in our Privacy Policy: https://www.solventum.com/en-us/home/legal/website-privacy-statement/applicant-privacy/

Job Description:

Role: Senior AI-ML Engineer / Data Scientist,

3M Health Care is now Solventum

At Solventum, we enable better, smarter, safer healthcare to improve lives. As a new company with a long legacy of creating breakthrough solutions for our customers' toughest challenges, we pioneer game-changing innovations at the intersection of health, material and data science that change patients' lives for the better while enabling healthcare professionals to perform at their best. Because people, and their wellbeing, are at the heart of every scientific advancement we pursue.

We partner closely with the brightest minds in healthcare to ensure that every solution we create melds the latest technology with compassion and empathy. Because at Solventum, we never stop solving for you.

The Impact You'll Make in this Role

As an Senior AI/ML Engineer - Supply Chain AI & Intelligent Automation , you will design, develop, and deploy Artificial Intelligence (AI), Machine Learning (ML), and Generative AI solutions that improve Supply Chain across functions. You will build scalable, production-ready AI applications that enable intelligent decision-making, automation, and operational efficiency.

In this role, you will develop Machine Learning models, AI Agents, and cloud-native AI solutions using AWS and Azure to solve complex supply chain challenges. You will collaborate with Supply Chain stakeholders, Lead Data Scientists, Cloud Architects, and Analytics Teams to translate business requirements into reliable, scalable AI solutions that deliver measurable business value.

Key Responsibilities

Machine Learning Solution Development

• Design, develop, and deploy scalable Machine Learning models and AI solutions to solve complex Supply Chain business challenges. Build end-to-end ML pipelines for forecasting, optimization, predictive analytics, anomaly detection, and intelligent automation, ensuring models are production-ready, reliable, and scalable.
• Design, develop, and deploy scalable Machine Learning models and AI solutions to solve complex Supply Chain business challenges. Build end-to-end ML pipelines for forecasting, optimization, predictive analytics, anomaly detection, and intelligent automation, ensuring models are production-ready, reliable, and scalable.

Agentic AI & Generative AI Engineering

• Design, build, test, and deploy AI Agents and multi-agent systems using frameworks such as Lang Graph, Lang Chain, Auto Gen, Crew AI, or similar technologies. Develop intelligent workflows that leverage LLMs, tool integration, memory, and orchestration to automate business processes and improve operational decision-making.
• Design, build, test, and deploy AI Agents and multi-agent systems using frameworks such as Lang Graph, Lang Chain, Auto Gen, Crew AI, or similar technologies. Develop intelligent workflows that leverage LLMs, tool integration, memory, and orchestration to automate business processes and improve operational decision-making.

Enterprise Data Engineering & AI Integration

• Develop robust data ingestion, transformation, and feature engineering pipelines to process structured, semi-structured, and unstructured enterprise data. Integrate enterprise knowledge repositories, knowledge graphs, vector databases, and intelligent document processing solutions to enable contextual AI insights, enhance retrieval capabilities, and support scalable Machine Learning and Generative AI applications.
• Develop robust data ingestion, transformation, and feature engineering pipelines to process structured, semi-structured, and unstructured enterprise data. Integrate enterprise knowledge repositories, knowledge graphs, vector databases, and intelligent document processing solutions to enable contextual AI insights, enhance retrieval capabilities, and support scalable Machine Learning and Generative AI applications.

Cloud AI Deployment & MLOps

• Deploy and manage AI and Machine Learning applications on AWS and Microsoft Azure. Build and maintain MLOps and LLMOps pipelines, including model versioning, CI/CD, automated deployment, monitoring and retraining to ensure scalable, secure, and high-performing production AI systems.
• Deploy and manage AI and Machine Learning applications on AWS and Microsoft Azure. Build and maintain MLOps and LLMOps pipelines, including model versioning, CI/CD, automated deployment, monitoring and retraining to ensure scalable, secure, and high-performing production AI systems.

Model Performance & AI Optimization

• Evaluate, monitor, and optimize Machine Learning models and Large Language Models (LLMs) using appropriate