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Senior Applied Scientist

Siemens -
Bellevue, WA

Job Details

Full-time
$167,443 - $226,073 a year

Qualifications

AI models
Engineering development testing
AI platforms (beyond public GPTs)
Computational framework
Collaboration with product development teams
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 Senior 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

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 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

6+ 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.

$167,443 $226,073 15%

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