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Interpretability Ai Jobs in Minnesota (NOW HIRING)

DEVELOPER L4

Minneapolis, MN · On-site

$60K - $135K/yr

... interpretability. • Knowledge of Azure, AWS, and GCP cloud AI services. • Ability to communicate technical AI concepts effectively to business and leadership stakeholders. Preferred Skills • ...

Interpretability Ai information

What is interpretability in AI?

Interpretability in AI refers to the ability to understand and explain how artificial intelligence systems, especially complex models like neural networks, make their decisions. It helps researchers, developers, and end-users to trust AI systems by making their inner workings more transparent. Interpretability is crucial in sensitive fields such as healthcare and finance, where decisions need to be justified and understood. Techniques for interpretability include feature importance, visualization, and model simplification. Improving interpretability can lead to safer, fairer, and more accountable AI systems.

What are the key skills and qualifications needed to thrive as an AI interpretability specialist, and why are they important?

To thrive as an AI Interpretability Specialist, you need expertise in machine learning, statistics, and data analysis, often backed by a degree in computer science, mathematics, or a related field. Familiarity with interpretability frameworks (like LIME, SHAP), deep learning libraries (such as TensorFlow or PyTorch), and experience with model evaluation tools are typically required. Strong problem-solving abilities, communication skills, and intellectual curiosity help bridge the gap between technical results and stakeholder understanding. These competencies are essential to ensure AI models are transparent, trustworthy, and aligned with ethical standards.

What are the main challenges faced when working in interpretability AI roles, and how can professionals address them?

Professionals in Interpretability AI often face the challenge of translating complex machine learning models into understandable insights for both technical and non-technical stakeholders. This requires not only a deep understanding of algorithms but also strong communication skills to bridge the gap between data scientists, engineers, and decision-makers. Additionally, balancing the trade-off between model accuracy and interpretability can be tricky, as more interpretable models may sometimes be less accurate. Collaborating closely with cross-functional teams and staying updated with the latest interpretability techniques can help overcome these challenges and add value to AI projects.

What is the difference between Interpretability Ai vs Data Scientist?

AspectInterpretability AiData Scientist
Required CredentialsTypically a background in AI, machine learning, or data analysis; often a master's or PhD in related fieldsDegree in computer science, statistics, or related fields; often a master's or PhD
Work EnvironmentResearch labs, AI development teams, tech companies focusing on explainable AIData analysis, modeling, and insights generation across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, tech, consulting, and more

Interpretability Ai specialists focus on making AI models transparent and understandable, often working on explainability tools. Data Scientists analyze data, build models, and generate insights. While both roles require strong analytical skills, Interpretability Ai emphasizes explainability techniques, whereas Data Scientists focus on data analysis and modeling across diverse industries.

What are popular job titles related to Interpretability Ai jobs in Minnesota?

For Interpretability Ai jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Interpretability Ai jobs in Minnesota look for?

The top searched job categories for Interpretability Ai jobs in Minnesota are:

Infographic showing various Interpretability Ai job openings in Minnesota as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution.

Principal Engineer, AI and Machine Learning Software

Murata Manufacturing Co., Ltd.

Saint Paul, MN • On-site

$141 - $160/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 24 days ago


Job description

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Principal Engineer, AI and Machine Learning Software

Location:

St. Paul, MN, US, 55128

Murata Viosis a global medical device company dedicated to creating a paradigm shift in the way healthcare is delivered. Through the utilization of our internet-of-things medical-grade sensors and virtual patient care services, we plan to lower the cost of healthcare and improve patient outcomes. Murata Viosis seeking qualified individuals who contribute to our vision through sound product development engineering practices and passionate sales and marketing leadership.

Why Consider This Job Opportunity

Murata Vios is looking for a talented and motivated Principal Engineer specializing in AI and Machine Learning (ML). This role combines technical leadership with hands‑on development, defining the technical direction for AI/ML technologies. The AI & MI Principal Engineer designs, develops, and deploys innovative algorithms that enhance our medical devices and improve patient outcomes. This position works alongside cross-functional teams to deliver impactful solutions while adhering to regulatory standards.

Workplace Policy

Hybrid from Woodbury, Minnesota

What To Expect (Essential Job Responsibilities)
  • Lead the architecture and design of scalable AI platforms and production of ML systems.
  • Provide technical leadership and mentorship to AI/ML engineers.
  • Lead technical reviews and make key architectural decisions for AI-enabled products.
  • Evaluate and introduce emerging AI technologies that provide competitive advantage.
  • Partner with product management, clinical teams, quality, regulatory affairs, and software engineering to define long-term AI/ML technology strategy and product roadmaps.
  • Collaborate with software engineers to integrate AI/ML models into existing software frameworks and ensure seamless operation of medical device systems.
  • Design and develop machine learning algorithms that analyze medical data (e.g., images, biosignals) to support diagnostic and predictive capabilities.
  • Design, develop, and deploy scalable AI/ML pipelines from research through production, ensuring reproducibility, reliability, and maintainability.
  • Develop and optimize deep learning models for biomedical signal, time-series, and medical image analysis.
  • Evaluate, validate, and optimize models for robustness, interpretability, and regulatory compliance.
  • Collect, preprocess, and analyze large biomedical datasets, ensuring data integrity and compliance with privacy regulations (e.g., HIPAA).
  • Optimize existing machine learning models for performance, accuracy, and efficiency; conduct testing and validation according to regulatory standards (e.g., ISO 13485).
  • Prepare technical documentation such as design specifications, testing protocols, and user manuals in compliance with medical device regulations.
  • Keep abreast of the latest advancements in AI/ML technologies and best practices as well as regulatory changes pertinent to the medical device industry.
  • Provide ongoing support and enhancements for deployed models and algorithms based on user feedback and performance monitoring.
What Is Required (Qualifications)
  • Ph.D. with 7+ years or Master’s degree with 15+ years of relevant industry experience in computer science, Software Engineering, Machine Learning, Biomedical Engineering, or a related field.
  • Experience developing deep learning models using architectures such as CNNs, RNNs/LSTMs, transformers, and other modern techniques for biomedical signal, time-series, and medical image analysis.
  • Experience with MLOps practices, including experiment tracking, model versioning, CI/CD for machine learning, automated training pipelines, and monitoring model performance in production.
  • Experience deploying AI/ML models using cloud platforms and containerized technologies such as AWS, Azure, Docker, Kubernetes, ONNX, or TensorRT.
  • Knowledge of explainable AI (XAI), model interpretability, AI risk management, and validation practices for regulated healthcare and medical device applications.
  • Experience in digital signal processing (DSP), signal conditioning, feature extraction, time-series analysis, and statistical signal processing. Experience with wavelet analysis and frequency-domain techniques is preferred.
  • Experience with foundation models, large language models (LLMs), retrieval-augmented generation (RAG), or multimodal AI applications is a plus.
  • Proficiency in MATLAB, Linux, Python.
  • Experience with software engineering best practices, including object-oriented design, code reviews, unit and integration testing, version control (Git), and Agile development methodologies.
  • Knowledge of FDA regulations, ISO standards (e.g., ISO 13485), and compliance requirements applicable to medical devices.
  • Excellent problem-solving and communication skills with a strong analytical mindset.
Other

Minimum Salary: $140,967.00

Maximum Salary: $160,000.00

  • Comprehensive benefits package including medical, dental, and vision insurance.
  • Generous Paid Time Off including paid holidays and floating holidays.
  • 401(k) employer match on retirement planning.
  • Hybrid working schedule for eligible positions.
  • Tuition reimbursement on approved programs.
  • Flexible and health spending accounts.

Create a better life for patients, clinicians, and hospital administrators by joining the Murata Viosteam. Murata Viosoffers competitive compensation and comprehensive benefits.

Equal Opportunity/Affirmative Action Employer – M/F/Disabilities/Veterans

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