Here at Siemens, we take pride in enabling sustainable progress through technology. We do this through empowering customers by combining the real and digital worlds. Improving how we live, work, and move today and for the next generation! We know that the only way a business thrives is if our people are thriving. That’s why we always put our people first. Our global, diverse team would be happy to support you and challenge you to grow in new ways. Who knows where our shared journey will take you?  

As a Principal Scientist, you will set the scientific direction and advance state‑of‑the‑art methods that power intelligent, interactive systems operating in real industrial environments.

This is a high-impact role for a research leader who thrives at the intersection of fundamental ML, data, and systems. You’ll partner closely with software engineers, product managers, and executives to define the scientific roadmap, architect evaluation frameworks, and translate cutting‑edge research into production-grade capabilities that scale. Your work will directly shape multiple teams and the product trajectory.

This position is remote with a preference for location in Seattle, WA.

You’ll make an impact by:

• Owning the scientific roadmap across core AI capabilities (multimodal perception, language/agentic reasoning, time-series modeling), with clear hypotheses, milestones, and success metrics.
• Designing robust evaluation & benchmarking for generative and predictive models (offline metrics, online A/B, safety & robustness tests), and institutionalizing scientific rigor across teams.
• Bridging research to production, partnering with engineering to harden models and pipelines (data readiness, optimization, inference runtime, observability) for industrial-grade reliability.
• Leading applied research projects end-to-end—from literature review and method selection to ablations, scaling, and productization—while making pragmatic tradeoffs under uncertainty.
• Mentoring scientists and engineers, running technical reviews, and raising the bar on reproducibility, documentation, and experiment hygiene.
• Championing Responsible AI, including bias detection, model risk management, guardrails, and human‑in‑the‑loop controls for safety-critical use cases.
• Proactively de‑risking scaling bottlenecks (data quality, latency/throughput, cost, drift) and influencing long-term architecture decisions with evidence.

You’ll win us over by having the following qualifications:

Basic Qualifications

• 10+ years in AI/ML research or applied science, with hands-on experience training, evaluating, and shipping models to production.
• Demonstrated impact designing/scaling ML systems (distributed training, model serving, online evaluation) and real-time applications.
• Proven ability to lead scientific strategy and cross‑team architecture efforts; strong systems thinking.
• Proficiency in Python and modern ML stacks; deep understanding of optimization, generalization, performance, and fault‑tolerance in ML systems.
• Clear communication and the ability to influence across engineering, product, and leadership.

Preferred Qualifications

• Experience connecting ML research to products in the physical world (manufacturing, automation, robotics, IIoT, edge).
• Track record in multimodal ML (text, vision, 3D/CAD, time series), retrieval‑augmented generation, or agentic workflows.
• Publications, patents, open‑source contributions, or significant internal tech transfers; ability to mentor senior/staff scientists.
• Familiarity with Responsible AI frameworks (fairness/robustness testing, guardrails, model risk).
• Comfort collaborating within a global, cross‑functional organization.