About this role
Summary: Join the Robotics & Simulation AI team to define evaluation metrics, build observability pipelines, and conduct data science experiments on production AI Copilots. This role focuses on AI quality measurement, stability research, and domain-specific AI research for industrial robotics.
Company Overview
Siemens Digital Industries Software is a leading provider of solutions for the design, simulation, and manufacture of products across many different industries. Formula 1 cars, skyscrapers, ships, space exploration vehicles, and many of the objects we see in our daily lives are being conceived and manufactured using our Product Lifecycle Management (PLM) software.
Position Overview
We are looking for a highly motivated AI Research Student for our Robotics & Simulation AI team. You will be passionate about data science, AI quality measurement, and the intersection of AI with high-accuracy industrial domains. This role is ideal for someone who grows with challenging existing assumptions, defining rigorous evaluation methodologies, and pushing AI systems toward measurable reliability. You will combine strong data science and research skills with hands-on experimentation in a production AI product that controls robotic manufacturing simulations.
Key Responsibilities
AI Quality & Stability Research
- Define and implement metrics to measure the stability, accuracy, and reliability of our production AI Copilot (PSCoPilot)
- Design evaluation frameworks for AI agents operating in safety-critical robotics and simulation environments
- Build observability and tracing pipelines using platforms like Langfuse to monitor Copilot performance, token usage, latency, and tool-calling success rates
- Analyze failure modes, hallucination patterns, and tool-calling accuracy across 48+ MCP-exposed robotic operations
- Develop automated regression and benchmark pipelines to track Copilot quality over time
Data Science & Experimentation
- Conduct statistical analysis on Copilot interactions (tool selection accuracy, collision detection correctness, path planning success rates)
- Research and apply techniques from AI evaluation literature (LLM-as-judge, human-in-the-loop validation, domain-specific benchmarks)
- Leverage LangChain and similar orchestration frameworks to prototype evaluation chains, structured agent workflows, and comparison experiments
- Explore how multi-layer agent architectures (fast triage + deep execution) affect accuracy and cost trade-offs
- Challenge the team with data-driven insights on where the Copilot underperforms and why
Domain AI Research
- Investigate how to improve AI reasoning for robotics tasks requiring high precision (welding, clearance checking, reachability analysis)
- Research grounding techniques that reduce errors in domains with zero tolerance for incorrect outputs
- Explore and apply new AI technologies (GenAI tools, AI coding assistants, agents, MCP-based solutions) to enhance Copilot capabilities
- Validate technical feasibility through hands-on experimentation with our production MCP bridge and two-layer streaming agent engine
Communication & Documentation
- Document findings, benchmarks, and technical recommendations
- Present results to technical and business partners
- Collaborate with the team to translate research insights into production improvements
Qualifications
- Currently pursuing a Master's degree or equivalent experience in AI, Data Science, Machine Learning, Computer Science, Statistics, or a related field with minimum 2 years until graduation
- Strong background in data science, statistical analysis, and experiment design
- Proficiency in Python with experience using LLM orchestration platforms (LangChain, AWS Bedrock, Azure OpenAI)
- Familiarity with LLM evaluation techniques, prompt engineering, or AI agent architectures
- Experience with or strong interest in defining quality metrics for AI systems
- Fast learner with strong self-motivation and ability to challenge technical decisions with data
- Proficiency in English
Preferred
- Experience with AI observability platforms (Langfuse, LangSmith, or similar)
- Exposure to robotics, simulation, manufacturing, or safety-critical AI domains
- Familiarity with MCP (Model Context Protocol), AI coding assistants, or multi-agent systems
Why Us
We are Siemens: At Siemens Software, flexibility is how we work—hybrid by default, built on trust and autonomy. Together, 30,000 people across more than 200 countries build technology that shapes the real world. You'll grow through real projects, strong technical peers, and global mobility, backed by the scale and benefits of an industrial software leader. We're committed to equality and inclusion, and we hire based on merit, skills, and impact. Bring your curiosity and creativity and help us shape tomorrow!
Compensation
The hourly rate for this position is ILS 90 per hour for students pursuing a bachelor's degree or equivalent experience during their first year of employment with Siemens. Starting from their second year of employment, students pursuing a bachelor's degree will receive ILS 100 per hour. Students pursuing a master's degree or equivalent experience will receive ILS 100 per hour.
Siemens offers health and wellness benefits to employees; you can access the benefits available in your country via the link: [benefits](https://jobs.sw.siemens.com/benefits/)
Diversity and Inclusion
We are an equal opportunities employer and do not discriminate unlawfully on the grounds of age, disability, gender, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, sexual orientation, or trade union membership. We value diverse perspectives and welcome applications from candidates of all backgrounds.
Siemens Software. Transform the Everyday
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