Senior Principal Applied Scientist at Siemens

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 Senior Principal Applied Scientist, you set the scientific direction for the pod. You decide which problems are worth solving with ML, what methods to apply, how to evaluate them, and how to move them from a research result to a model that runs in production. You are accountable for the science: the rigor, the evidence, and the outcomes. This is a senior individual contributor role. Your impact comes from owning the hypotheses, the evaluation, and the path from research to production, and from raising the scientific bar across the team. Key responsibilities • Set the applied science roadmap for the pod across the core AI capabilities the product depends on, for example multimodal perception, computer vision, language and agentic reasoning, time series modeling, control • Convert product and system requirements into clear research questions, hypotheses, and success metrics • Design and own the evaluation and benchmarking frameworks for generative and predictive models, including offline metrics, online experimentation, and robustness testing in industrial conditions • Lead applied research projects end to end, from literature review and method selection through experimentation, ablation, and productization • Work with engineers to take models into production grade pipelines: data readiness, optimization, inference, observability • Influence architectural and system decisions with scientific evidence and tradeoff analysis • Identify and de-risk scaling challenges: data quality, model drift, latency, throughput, cost, safety • Mentor scientists and engineers on experimentation rigor, reproducibility, and documentation • Champion responsible and trustworthy AI: bias detection, model risk management, human in the loop controls Basic qualifications • 10+ years in applied machine learning, AI research, or data science, with a track record of models that shipped to production and made an impact • Strong foundation in machine learning theory and practice across training, evaluation, and deployment • Demonstrated experience setting the science direction for a portfolio of work and shipping it through to production with engineering teams • Proficiency in Python and modern ML frameworks and toolchains • Track record of building evaluation and benchmarking that the team can run a roadmap against • Clear written and verbal communication, with the ability to explain complex ML concepts to engineers, product managers, and senior leaders Preferred qualifications • Experience setting science direction across multiple capability areas at the same time • Experience bringing applied research into real world products in industrial or physical domains: manufacturing, automation, robotics, energy, mobility, infrastructure, healthcare • Breadth across multimodal ML, generative AI, retrieval, agentic workflows, control, or planning • Scientific ML for physical systems: surrogate modeling, operator learning, physics-informed ML, geometry-aware ML, differentiable simulation, AI for semiconductor/EDA • Experience standing up evaluation, online experimentation, or production monitoring as practices, not just for a single model • Publications, patents, open source contributions, or significant internal technology transfers that the field can point to • Experience hiring and mentoring senior or staff level scientists • 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. You’ll Benefit From Siemens offers a variety of health and wellness benefits to our employees. Details regarding our benefits can be found here: benefitsquickstart.com The pay range for this position is $197,268 - $267,036 annually with a target incentive of 20% of the base salary. The actual wage offered may be lower or higher depending on budget and candidate experience, knowledge, skills, qualifications, and premium geographic location. Equal Employment Opportunity Statement Siemens is an Equal Opportunity Employer encouraging inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability unrelated to ability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, order of protection status, protected veteran or military status, or an unfavorable discharge from military service, and other categories protected by federal, state or local law. EEO is the Law Applicants and employees are protected from discrimination on the basis of race, color, religion, sex, national origin, or any characteristic protected by Federal or other applicable law. Reasonable Accommodations If you require a reasonable accommodation in completing a job application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please fill out the accommodations form by clicking on this link Accommodation for disability form . If you’re unable to complete the form, you can reach out to our AskHR team for support at 1-866-743-6367. Please note our AskHR representatives do not have visibility of application or interview status. Pay Transparency Siemens follows Pay Transparency laws. Application Deadline This role will be posted for a minimum of five (5) days from the original posting date. The posting timeline may change based on applicant volume to ensure we attract and consider a strong and representative candidate pool. California Privacy Notice California residents have the right to receive additional notices about their personal information. To learn more, click here . Criminal History Qualified applications with arrest or conviction records will be considered for employment in accordance with applicable local and state laws.

Requirements

Must-haves

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.
This is a senior individual contributor role. Your impact comes from owning the hypotheses, the evaluation, and the path from research to production, and from raising the scientific bar across the team.
Set the applied science roadmap for the pod across the core AI capabilities the product depends on, for example multimodal perception, computer vision, language and agentic reasoning, time series modeling, control
Convert product and system requirements into clear research questions, hypotheses, and success metrics
Design and own the evaluation and benchmarking frameworks for generative and predictive models, including offline metrics, online experimentation, and robustness testing in industrial conditions
Lead applied research projects end to end, from literature review and method selection through experimentation, ablation, and productization
Work with engineers to take models into production grade pipelines: data readiness, optimization, inference, observability
Influence architectural and system decisions with scientific evidence and tradeoff analysis
Identify and de-risk scaling challenges: data quality, model drift, latency, throughput, cost, safety
Mentor scientists and engineers on experimentation rigor, reproducibility, and documentation
Champion responsible and trustworthy AI: bias detection, model risk management, human in the loop controls
10+ years in applied machine learning, AI research, or data science, with a track record of models that shipped to production and made an impact
Strong foundation in machine learning theory and practice across training, evaluation, and deployment
Demonstrated experience setting the science direction for a portfolio of work and shipping it through to production with engineering teams
Proficiency in Python and modern ML frameworks and toolchains
Track record of building evaluation and benchmarking that the team can run a roadmap against

Nice-to-haves

Experience setting science direction across multiple capability areas at the same time
Experience bringing applied research into real world products in industrial or physical domains: manufacturing, automation, robotics, energy, mobility, infrastructure, healthcare
Breadth across multimodal ML, generative AI, retrieval, agentic workflows, control, or planning
Scientific ML for physical systems: surrogate modeling, operator learning, physics-informed ML, geometry-aware ML, differentiable simulation, AI for semiconductor/EDA
Experience standing up evaluation, online experimentation, or production monitoring as practices, not just for a single model
Publications, patents, open source contributions, or significant internal technology transfers that the field can point to
Experience hiring and mentoring senior or staff level scientists
Experience working with globally distributed research, product, or engineering organizations

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlpython

Platform: avature
Effort: medium

Benefits

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Wellness