Senior AI ML Engineer

IND KCI Medical India Private limited; Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Solventum in Bangalore is seeking a Senior AI-ML Engineer/Data Scientist to design, deploy, and operate scalable ML/AI solutions across the supply chain domain. You will build end-to-end pipelines, develop agentic AI workflows, and integrate enterprise data with modern AI tooling in production.

The role requires strong Python expertise, hands-on cloud experience (Azure, AWS), and a solid track record delivering Generative AI projects with responsible AI practices.

Qualifications

• Bachelor’s degree in CS, AI, or related field with 7+ years of ML/AI experience or master’s with 5+ years.
• Experience designing, developing, deploying ML/AI solutions in production environments.

Responsibilities

• Design, develop, and deploy scalable ML models and AI solutions for Supply Chain challenges.
• Build end-to-end ML pipelines for forecasting, optimization, predictive analytics, anomaly detection, and automation.
• Develop AI Agents and multi-agent workflows using Lang Graph, Lang Chain, Auto Gen, Crew AI.
• Ingest, transform, and engineer features from enterprise data; enable contextual AI insights.
• Deploy AI apps on AWS/Azure with MLOps/LLMOps pipelines and monitoring.

Skills

Python

Machine Learning

Generative AI

LLMs

Cloud platforms

Docker

Kubernetes

Data Science

Education

Bachelor’s degree in Computer Science or related

Master’s degree (preferred)

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.

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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• Model Performance & AI Optimization Evaluate, monitor, and optimize Machine Learning models and Large Language Models (LLMs) using appropriate performance metrics. Improve model accuracy, reduce inference latency, optimize cloud resource utilization, and implement responsible AI practices to ensure reliable and cost-effective AI solutions.
• Model Performance & AI Optimization Evaluate, monitor, and optimize Machine Learning models and Large Language Models (LLMs) using appropriate performance metrics. Improve model accuracy, reduce inference latency, optimize cloud resource utilization, and implement responsible AI practices to ensure reliable and cost-effective AI solutions.
• Technical Collaboration & Engineering Excellence Partner with Supply Chain stakeholders, Data Scientists, Software Engineers, Cloud Architects, Product Managers, and Digital Transformation teams to translate business requirements into scalable AI-ML solutions. Establish engineering standards, contribute to architecture and code reviews, create technical documentation.
• Technical Collaboration & Engineering Excellence Partner with Supply Chain stakeholders, Data Scientists, Software Engineers, Cloud Architects, Product Managers, and Digital Transformation teams to translate business requirements into scalable AI-ML solutions. Establish engineering standards, contribute to architecture and code reviews, create technical documentation.

Your Skills and Expertise

Bachelor’s degree in computer science, Software Engineering, AI, or related field and 7+ years of professional experience in Machine Learning, Artificial Intelligence, Data Science, or Ai Engineering or a master’s degree with relevant industry experience and 5+ years of experience. Strong hands‑on expertise in Python with proven experience designing, developing, deploying, and optimizing scalable Machine Learning and AI solutions in production environments, including predictive modelling, forecasting, optimization, feature engineering, model evaluation, monitoring, and lifecycle management using cloud platforms such as Azure, Data Bricks and AWS. Experience building and deploying Generative AI applications and Agentic AI workflows in production using frameworks such as Lang Graph, Lang Chain, Auto Gen, Crew AI, or similar technologies production grade in AWS / Azure cloud. Practical experience with Large Language Models (LLMs), Prompt Engineering, RAG, AI evaluation techniques, and responsible AI practices. Strong understanding of system design patterns, microservices architecture, APIs, containerization (Docker), Kubernetes, and infrastructure automation. Experience implementing AI observability and evaluation using tools such as Azure AI Foundry, Azure Monitor, Azure ML Monitoring, AWS CloudWatch, ML flow, Lang Smith, Prometheus, Grafana, or Open Telemetry to monitor AI quality, latency, reliability, cost, and operational performance. Experience working with enterprise data platforms, data pipelines, SQL, and distributed data processing frameworks to support AI/ML solutions.

Preferred Qualifications

• Hands-on experience developing AI/ML solutions for Supply Chain, Healthcare, or other enterprise domains.
• Experience implementing MLOps and LLMOps practices, including model versioning, CI/CD pipelines, automated deployment, monitoring, observability, and AI lifecycle management.
• Strong understanding of system design patterns, microservices architecture, APIs, containerization (Docker), Kubernetes, and infrastructure automation.
• Familiarity with AI governance, model explainability, data security, privacy, and Responsible AI practices.

Location - Bangalore (Hybrid) Travel - 10-20%

A new healthcare company with a rich history. With more than 70 years of delivering healthcare innovations, we continue to move the industry forward by helping to solve our customers’ biggest challenges. 20,000+ employees worldwide. Solventum relies on the courage and the boundless insights of professionals worldwide to achieve exceptional results for our customers and those who rely on them. Healthcare that leads with heart and humility starts with listening and never finishes, only evolves. As long as healthcare challenges remain unsolved, we will be here, united by empathy and a relentless belief that countless lives are improved through our work. Operations in 38 countries. Driven by our dedication to improved outcomes for all we serve, we break through by making unprecedented connections that impact lives. In more than 300 offices and facilities around the world, we work closely with customers and partners to create positive healthcare outcomes that transcend borders. To realize our shared vision, we harness diverse talents and perspectives from every background to not only address our customers’ most urgent priorities but anticipate the needs of the future