Senior Applied Scientist

Siemens Mobility; Bellevue (WA); On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

Health benefits

Job summary

Siemens Mobility is seeking a senior applied machine learning researcher to advance capabilities such as perception, language and agents, time series, and control in production-grade systems. You will lead end-to-end research projects, develop evaluation pipelines, and work with engineers to translate research into robust production pipelines with strong emphasis on reproducibility and safety.

The role requires 6+ years in ML/AI research with a track record of shipping impactful models,

Qualifications

• 6+ years in applied ML, 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
• 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

Responsibilities

• Contribute to 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 youown: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
• Identifyand 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

Job description

Key responsibilities

• Contribute to 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 youown: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
• Identifyand 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
• 6+ years in applied machine learning, AI research, or data science, with models that shipped to production and made an impact
• Strong foundationin 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
• Proficiencyin Python and modern ML frameworks and toolchains
• Strong partnershiptrack recordwith 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
• Deepexpertisein 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 sourcecontributions, 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.

You’ll Benefit From

Siemens offers a variety of health and wellness benefits to our employees. Details regarding our benefits can be found here: https://www.benefitsquickstart.com/siemens/index.html
The pay range for this position is $167,443 - $226,073 annually with a target incentive of 10% 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 Accommodationfor 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.

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.

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Pay Transparency

Siemens follows Pay Transparency laws.

Criminal History

Qualified applications with arrest or conviction records will be considered foremployment in accordance with applicable local and state laws.

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