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AI/ML Implementation Support Engineer

Référence du poste
505359
Publié depuis
06-Mai-2026
Domaine d'activité
Recherche et développement
Entreprise
Siemens Healthcare Private Limited
Niveau d'expérience
Expérimenté
Type de poste
Temps plein
Mode de travail
Au bureau / sur site uniquement
Type de contrat
Contrat à durée indéterminée (CDI)
Localisation(s)
  • Bangalore - Karnataka - Inde
Qualification: B.E/MCA/ME degree (CSE/IS/DS)

Experience:  

  • 4 – 7 years of Hands-on experience software development, scripting with Python, SQL, or similar scripting languages, data workflows, DevOps, or related technical activities.
  • Exposure to latest AI/ML technologies, data platforms, or cloud environments and exposure in building AI agents.

Responsibility:  The role serves as a bridge between developers, data scientists, tool owners, legal experts and project managers, ensuring high quality tool usage, smooth platform operations, and compliance with internal and regulatory requirements

  • Enable R&D teams to efficiently develop, deploy, and operate data-driven and AI enabled solutions by providing expert support, tool onboarding, platform configuration, and technical guidance across the Big Data & AI ecosystem. 
  • Troubleshoot technical issues, analyze root causes, and coordinate fixes with tool owners, developers, and central IT
  • Onboard new users and teams to Big Data/AI platforms, including access management, environment setup, and best practices. 
  • Develop guidance, FAQs, and training materials to improve adoption and maturity in the business line
  • Support updates, configurations, and maintenance of tools in alignment with internal quality and security requirements
  • Support alignment with regulatory requirements applicable to software in medical devices (e.g., IEC 62304, ISO 13485) when relevant for AI tool environments
Skills:

Mandatory:
  • Familiarity with Python, SQL, or similar scripting languages. 
  • Basic understanding of machine learning concepts and model lifecycle
  • Knowledge on AI/ML concepts and exposure to frameworks like scikit‑learn, TensorFlow, PyTorch
  • Exposure to pipelines, automation, or data processing workflows (e.g., CI/CD, ETL, basic data engineering tasks) 
Optional:
  • Continuous learning attitude, especially towards AI and data technologies
  • Understanding of Cybersecurity concepts as per ISO Standards are highly recommended & Ability to handle vulnerable items related to Application layer. 
  • Understanding of ISO 27001 information security standards, ISO 13485:2016 and 21CFR requirements for quality management systems, particularly relevant to medical device software. 
  • Passion for exploring new tools and technologies with quick learning skills