Senior AI ML Engineer

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 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. 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. 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% Solventum is committed to maintaining the highest standards of integrity and professionalism in our recruitment process. Applicants must remain alert to fraudulent job postings and recruitment schemes that falsely claim to represent Solventum and seek to exploit job seekers. Please note that all email communications from Solventum regarding job opportunities with the company will be from an email with a domain of @solventum.com. Be wary of unsolicited emails or messages regarding Solventum job opportunities from emails with other email domains. Please note: your application may not be considered if you do not provide your education and work history, either by: 1) uploading a resume, or 2) entering the information into the application fields directly. Solventum Global Terms of Use and Privacy Statement Carefully read these Terms of Use before using this website. Your access to and use of this website and application for a job at Solventum are conditioned on your acceptance and compliance with these terms. Please access the linked document by clicking here. Before submitting your application you will be asked to confirm your agreement with the terms. 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