Applied Scientist

New York

About the role

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.

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
• Contribute to 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

Requirements

• 4+ 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

Qualifications

• Clear written and verbal communication with engineers, product managers, and senior leaders
• 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
• Hands-on experience building evaluation pipelines, running online experiments, or instrumenting production monitoring for a model you owned
• Publishations, patents, open source contributions, or significant internal technology transfers
• Experience working with globally distributed research, product, or engineering organizations

Benefits

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.

Pay

The pay range for this position is $182,600 - $216,700 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.

Reasonable Accommodations

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Pay Transparency

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