Siemens

Senior Principal Applied Scientist

Siemens$197K — $267K *
Technical Services
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years in applied machine learning, AI research, or data science with impactful production models.
  • Strong foundation in machine learning theory and practice including training and deployment.
  • Experience in setting scientific direction for projects and bringing them to production.
  • Proficiency in Python and modern ML frameworks.
  • Proven record of developing evaluation and benchmarking practices for the team.
  • Excellent written and verbal communication skills for conveying complex ML concepts.

Responsibilities

  • Set the applied science roadmap for core AI capabilities in the pod.
  • Translate product requirements into research questions and success metrics.
  • Design evaluation frameworks for generative and predictive models.
  • Lead end-to-end applied research projects from literature review to productization.
  • Collaborate with engineers to integrate models into production pipelines.
  • Provide scientific evidence for architectural and system decisions.
  • Identify and mitigate scaling challenges and model risks.
  • Mentor team members on rigor and documentation in experimentation.
  • Promote responsible and trustworthy AI practices.

Benefits

  • Comprehensive health and wellness benefits available.
  • Opportunities for professional development and continuing education.
  • Access to a variety of employee assistance programs.
Full Job Description
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.

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 $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.

About Siemens

Siemens AG is a German multinational conglomerate company headquartered in Munich and the largest industrial manufacturing company in Europe with branch offices abroad. The principal divisions of the company are Industry, Energy, Healthcare, and Infrastructure & Cities, which represent the main activities of the company. The company is a prominent maker of medical diagnostics equipment and its medical health-care division, which generates about 12 percent of the company's total sales, is its second-most profitable unit, after the industrial automation division. The company is a component of the Euro Stoxx 50 stock market index. Siemens and its subsidiaries employ approximately 385,000 people worldwide and reported global revenue of around €87 billion in 2019 according to its earnings release.
Learn more about Siemens
Size
305,000 employees
Industry
Founded
1847
NASDAQ

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