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Senior AI ML Engineer

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Senior AI ML Engineer in Others

  • Solventum
  • Full time
  • Email
  • Bengaluru, India

Responsibilities

  • Design, develop, and deploy scalable machine learning models and end-to-end ML pipelines for supply chain forecasting, optimization, predictive analytics, anomaly detection, and intelligent automation.
  • Build and deploy AI agents and multi-agent systems using LLMs, tool integration, memory, orchestration, and frameworks such as LangGraph, LangChain, AutoGen, and CrewAI.
  • Develop data ingestion, transformation, feature engineering, enterprise data integration, knowledge graph, vector database, and intelligent document processing solutions.
  • Deploy and manage AI and machine learning applications on AWS and Azure while building MLOps and LLMOps pipelines for versioning, automated deployment, monitoring, and retraining.
  • Evaluate and optimize machine learning models and LLMs for accuracy, inference latency, cloud resource utilization, reliability, and cost.
  • Implement AI observability and evaluation capabilities and contribute to system architecture, engineering standards, code reviews, and technical documentation.
  • Partner with supply chain stakeholders, data scientists, software engineers, cloud architects, product managers, and digital transformation teams to deliver scalable AI/ML solutions.

Requirements

  • Bachelor’s degree in computer science, software engineering, AI, or a related field with 7+ years of professional experience, or a master’s degree with relevant industry experience and 5+ years of experience.
  • Strong hands-on Python experience developing, deploying, and optimizing production machine learning and AI solutions, including predictive modeling, forecasting, optimization, feature engineering, model evaluation, monitoring, and lifecycle management.
  • Experience building and deploying production-grade generative AI applications and agentic AI workflows in AWS or Azure using frameworks such as LangGraph, LangChain, AutoGen, or CrewAI.
  • Practical experience with large language models, prompt engineering, retrieval-augmented generation, AI evaluation techniques, and responsible AI practices.
  • Understanding of system design patterns, microservices architecture, APIs, Docker, Kubernetes, and infrastructure automation.
  • Experience with AI observability and evaluation tools such as Azure AI Foundry, Azure Monitor, Azure ML Monitoring, AWS CloudWatch, MLflow, LangSmith, Prometheus, Grafana, or OpenTelemetry.
  • Experience with enterprise data platforms, data pipelines, SQL, and distributed data processing frameworks.
  • Preferred qualifications include AI/ML experience in supply chain, healthcare, or other enterprise domains; MLOps and LLMOps experience; and familiarity with AI governance, model explainability, data security, privacy, and responsible AI.

Benefits

  • Hybrid work arrangement in Bangalore.
  • 10–20% travel required.

Solventum

At Solventum, we enable better, smarter, safer healthcare to improve lives. We never stop solving for you.

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