Principal Applied Scientist

Principal Applied Scientist Siemens - 4.0 Bellevue, WA Job Details Full-time $197,268 - $267,036 a year 23 hours ago Qualifications AI models Engineering development testing AI platforms (beyond public GPTs) Computational framework Collaboration with product development teams Machine intelligence Model deployment Engineering research Model training Machine learning libraries Model evaluation Machine learning frameworks Prototypes Python Full Job Description 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 an applied science organization building the science behind them. The work sits at the intersection of machine learning research, real world data, and production systems running in industrial environments. As Principal Applied Scientist, you lead the science on a major capability area inside the pod. You take ambiguous problems through hypothesis, method selection, experimentation, and into models that run in production. You are hands on with the modeling, and you are accountable for the rigor and the outcome. This is a senior individual contributor role. You will work in close partnership with engineers and product managers who turn your work into product. Key responsibilities Own one or more scientific capability areas end to end, for example perception, computer vision, language and agents, time series, control, planning, or evaluation Take problems from ambiguous product or system requirements through clear research questions, hypotheses, and success metrics Lead applied research projects: literature review, method selection, experimentation, ablation, error analysis, and productization Build and run the evaluation pipelines for the work you own: offline metrics, online experiments, robustness testing in industrial conditions Work with engineers to take models into production grade pipelines: data readiness, training infrastructure, inference, observability Make scientific tradeoffs in front of engineers and product managers, with evidence, and translate them into decisions the team can act on Identify and de-risk scaling challenges in your area: data quality, model drift, latency, throughput, cost, safety Raise the bar on experimentation rigor, reproducibility, and documentation across the team Apply responsible AI practices in your work: bias detection, model risk management, human in the loop controls Basic qualifications 8+ years in applied machine learning, AI research, or data science, with models that shipped to production and made an impact Strong foundation in machine learning theory and practice across training, evaluation, and deployment Demonstrated experience taking research from a paper or prototype into a model that runs reliably in production Proficiency in Python and modern ML frameworks and toolchains Strong partnership track record with engineering teams on data, training infrastructure, and inference Clear written and verbal communication with engineers, product managers, and senior leaders Preferred qualifications Experience applying ML in industrial or physical domains: manufacturing, automation, robotics, energy, mobility, infrastructure, healthcare Deep expertise in one of: multimodal ML, generative AI, retrieval augmented generation, agentic workflows, time series, control, or planning Scientific ML for physical systems: surrogate modeling, operator learning, physics-informed ML, geometry-aware ML, differentiable simulation, AI for semiconductor/EDA Hands-on experience building evaluation pipelines, running online experiments, or instrumenting production monitoring for a model you owned Publications, patents, open source contributions, or significant internal technology transfers Experience mentoring more junior scientists and engineers Experience working with globally distributed research, product, or engineering organizations About the

Team:

We are an early-stage engineering team solving hard technical problems at the intersection of AI, systems, and real-world interaction. We operate with high autonomy, collaborate closely across functions, and maintain high technical standards. Principal Engineers at our company are expected to lead by example, model engineering excellence, and shape both what we build and how we build it. Our Commitment to Equity and Inclusion in our

Diverse Global Workforce:

We value your unique identity and perspective. We are fully committed to providing equitable opportunities and building a workplace that reflects the diversity of society, while ensuring that we attract the best talent based on qualifications, skills, and experiences. We welcome you to bring your authentic self and transform the everyday with us. $197,268 $267,036 20%