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Principal Engineer, AI and Machine Learning Systems

ID de l'offre
509365
Publié depuis
08-Jun-2026
Organisation
Data & Artificial Intelligence
Domaine d'activité
Recherche et développement
Entreprise
Siemens Ltd., China
Niveau d'expérience
Expérimenté
Type de poste
Temps plein
Modalités de travail
Au bureau / sur site uniquement
Type de contrat
Contrat à durée déterminée (CDD)
Tout site Siemens situé dans
  • Chine
The role
Siemens builds the systems the physical world runs on: factories, power grids, buildings, trains, hospitals. Industrial and physical AI is a major opportunity in applied AI, and one of the harder ones to get right. There is a generation of AI-powered products to build.

We are forming engineering pods in China to build them. As Principal Engineer, you own the technical vision and system architecture for the AI-powered platforms the pod ships. You take evolving product and research requirements and turn them into systems that run reliably, scale economically, and stay maintainable as the work grows.

This is a senior individual contributor role for a deeply technical engineer who thrives in ambiguity. You are hands on. Your primary impact is through architectural leadership, technical judgment, and raising the engineering bar across the team.

Key responsibilities
  • Define the technical vision and system architecture for AI-powered platforms and products in the pod
  • Convert evolving product and research requirements into scalable, reliable ML systems
  • Partner with the Senior Principal Product Manager to align technical decisions with product strategy
  • Partner with the Senior Principal Applied Scientist and Principal Scientists to take models from experimentation into production grade systems
  • Own architectural decisions across model training, inference, data pipelines, and system integration
  • Identify critical risks early in performance, scalability, cost, and reliability, and drive solutions
  • Lead technical design reviews and influence architecture across multiple engineering teams
  • Establish best practices for ML system design, observability, testing, and long-term maintainability
  • Mentor senior engineers and serve as a technical role model in the organization

Basic qualifications
  • 8+ years of professional software engineering experience, including significant work on AI or ML-powered systems
  • Demonstrated experience designing, building, and scaling complex distributed systems
  • Strong understanding of the end-to-end machine learning lifecycle, including deployment and monitoring in production
  • Demonstrated ability to lead architectural efforts and influence technical direction beyond your immediate team
  • Proficiency in at least one backend systems programming language: Python, Go, Java, or similar
  • Strong system-level reasoning across performance, scalability, fault tolerance, and cost tradeoffs

Preferred qualifications
  • Experience bridging machine learning research and production engineering
  • Familiarity with generative AI systems, large language models, or multimodal pipelines
  • Experience building systems that interact with the physical world or real time environments
  • Background in ML infrastructure, model serving, inference optimization, or training infrastructure at scale
  • Experience mentoring senior engineers or acting as a technical lead across teams
  • Prior collaboration with globally distributed engineering or research organizations