Senior Software Engineer, AI and Machine Learning Systems

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 a Senior Software Engineer, you are one of the senior builders in the pod. You take significant chunks of the system from design through production and own them: data pipelines, training infrastructure, inference services, model serving, integration with industrial systems, or the product surface on top.

This is a hands-on engineering role. You write the code that ships. You partner with Principal Engineers on architecture, with Applied Scientists on getting models into production, and with Product Management on what the system needs to do. You are expected to make sound technical decisions inside your area without supervision.

Key Responsibilities

• Design, build, and operate significant components of the pod's AI-powered systems end to end
• Take ambiguous problems and turn them into working software: design, implementation, testing, deployment, and operation
• Partner with Applied Scientists to take models from experimentation into production: data readiness, training pipelines, inference, observability
• Own production quality in your area: reliability, latency, cost, monitoring, on-call, incident response
• Make sound technical decisions inside your area, and escalate decisions that affect broader architecture to your Principal Engineer partners
• Contribute to design reviews and technical direction across the pod
• Mentor more junior engineers and raise the engineering bar in code review, testing, and operational practices
• Help establish the engineering practices the pod runs on as it grows

• 5+ years of professional software engineering experience, with a track record of shipping and operating production systems
• Demonstrated experience building and operating distributed systems, services, or data systems in production
• Proficiency in at least one backend systems programming language: Python, Go, Java, or similar
• Strong fundamentals: data structures, algorithms, system design, debugging, performance
• Experience owning a non-trivial component end to end, including production operation
• Clear written and verbal communication with engineers, scientists, and product partners

• Experience working on AI or ML-powered systems: training infrastructure, model serving, inference optimization, data pipelines, ML observability, or applied ML in production
• Familiarity with generative AI systems, large language models, agents, or multimodal pipelines
• Experience building systems that interact with the physical world or real time environments
• Experience in industrial or regulated domains: manufacturing, automation, energy, mobility, infrastructure, healthcare
• Prior experience as a senior engineer in a small, ambiguous, fast-moving team