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Solventum
Solventum
Asistență medicalăConsultanțăLogistică
Solventum dezvoltă tehnologii și servicii medicale concepute pentru a susține îngrijirea medicală și orală într-un mod mai sigur și mai eficient. Portofoliul său include soluții avansate pentru îngrijirea rănilor, soluții chirurgicale și de sterilizare, produse pentru îngrijirea orală, servicii de informare și tehnologie medicală, precum și sisteme de purificare și filtrare pentru aplicații biofarmaceutice. Compania sprijină, de asemenea, profesioniștii din domeniul sănătății prin resurse educaționale și de instruire, combinând dezvoltarea produselor cu accentul pus pe siguranța pacienților, rezultatele clinice și eficiența operațională.
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Locurile de muncă ale companiei

Senior AI/ML Engineer – Bangalore Hybrid

Build production AI, machine learning, and agentic automation solutions for Solventum’s healthcare supply chain. Deploy scalable systems across AWS and Microsoft Azure.

INIndiaHibridNormă întreagăSeniorLimbă Obligatorie: englezăInginer de învățare automată
AWSAzureCloudDockerGrafanaKubernetesMicroserviciiPrometheusPythonSQL

Descriere

  • Create and deploy scalable machine learning models and AI solutions for complex supply chain problems
  • Develop end-to-end ML pipelines for forecasting, optimization, predictive analytics, anomaly detection, and intelligent automation
  • Design, test, and deploy AI agents and multi-agent systems with LangGraph, LangChain, AutoGen, CrewAI, or comparable frameworks
  • Build LLM-powered workflows with tool integration, memory, and orchestration to automate business processes
  • Create ingestion, transformation, and feature-engineering pipelines for structured, semi-structured, and unstructured enterprise data
  • Connect knowledge repositories, knowledge graphs, vector databases, and intelligent document-processing solutions
  • Deploy and operate AI and machine learning applications on AWS and Microsoft Azure
  • Maintain MLOps and LLMOps pipelines covering model versioning, CI/CD, automated deployment, monitoring, and retraining
  • Assess and improve ML models and LLMs for accuracy, latency, cloud resource use, reliability, and cost
  • Apply responsible AI practices
  • Partner with supply chain stakeholders, data scientists, software engineers, cloud architects, product managers, and digital transformation teams
  • Define engineering standards, participate in architecture and code reviews, and produce technical documentation

Cerințe

  • Bachelor’s degree in computer science, software engineering, AI, or a related field plus 7+ years of professional experience in machine learning, artificial intelligence, data science, or AI engineering
  • Alternatively, a master’s degree with relevant industry experience and 5+ years of experience
  • Advanced hands-on Python expertise
  • Background designing, developing, deploying, and optimizing scalable machine learning and AI solutions in production
  • Experience with predictive modeling, forecasting, optimization, feature engineering, model assessment, monitoring, and lifecycle management
  • Experience with cloud platforms including Azure, Databricks, and AWS
  • Production experience building and deploying generative AI applications and agentic AI workflows with LangGraph, LangChain, AutoGen, CrewAI, or similar technologies
  • Practical knowledge of large language models, prompt engineering, RAG, AI evaluation methods, and responsible AI
  • Strong understanding of system design patterns, microservices, 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
  • Willingness to travel 10–20%
  • Preferred: hands-on development of AI/ML solutions for supply chain, healthcare, or other enterprise domains
  • Preferred: experience applying MLOps and LLMOps practices
  • Preferred: familiarity with AI governance, model explainability, data security, privacy, and responsible AI practices

Beneficii

  • Hybrid work arrangement in Bangalore
  • Work on healthcare AI, machine learning, and data science solutions
  • Collaborate with technical and business teams across functions
  • Gain exposure to AWS and Microsoft Azure cloud platforms
  • Work across AI/ML, generative AI, agentic AI, MLOps, and LLMOps

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