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Scientific Machine Learning Jobs in Minnesota (NOW HIRING)

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

Bachelor's degree or Master's degree in Computer Science, Electrical and Computer Engineering, or ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Kitware

Machine Learning Engineer

Minneapolis, MN

$85K - $125K/yr

Bachelor's degree or Master's degree in Computer Science, Electrical and Computer Engineering, or ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

Bachelor's degree or Master's degree in Computer Science, Electrical and Computer Engineering, or ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Varsity Tutors

Machine Learning Tutor

Saint Paul, MN · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Minneapolis, MN · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Edina, MN · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Minnesota

Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What are the key skills and qualifications needed to thrive as a Scientific Machine Learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Minnesota? For Scientific Machine Learning jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Minnesota look for? The top searched job categories for Scientific Machine Learning jobs in Minnesota are:
What cities in Minnesota are hiring for Scientific Machine Learning jobs? Cities in Minnesota with the most Scientific Machine Learning job openings:
Scientific Machine Learning jobs near you
Machine Learning Engineer

Machine Learning Engineer

Solution Design Group

Minneapolis, MN

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 days ago

Job description

SDG is a high-performance software community. We are a team of collaborative and creative consultants who build and deliver custom software for some of the most recognizable local and national brands. In this role, you will be asked to leverage your current skills while also learning new ones. Working in over 500 different technologies and continually learning together, you can expect a one-of-a-kind and award-winning work experience. Our team at SDG has exceptional integrity and the desire to create the best possible customer solutions. We are proud to partner with our customers to consistently provide a successful working relationship as a high-performance team. 

We are adding a Machine Learning Engineer to our team! This person will play a key role in designing, implementing, and deploying machine learning models to solve complex problems and enhance our customer's products and services. You will be a part of a tight-knit technical community, giving you the opportunity to constantly grow your development amongst top technical talent. You will work closely with a cross-functional team of data scientists, software engineers, and domain experts to drive the development and deployment of machine learning solutions. SDG is looking for a hard worker with a team-oriented mindset, that has at least 3 years of experience and an in-depth understanding of machine learning and cloud data tools. A successful Machine Learning Engineer at SDG is a lifelong learner who is motivated to continually improve their craft and thrives amongst their fellow employee-owners.
SDG's Machine Learning Engineer's have proven experience with the following responsibilities. If you do too, we want to hear from you:
  • Design, implement, and optimize machine learning algorithms and models to address specific business challenges.
  • Collaborate with data engineers to preprocess and transform raw data into a format suitable for machine learning models. Conduct feature engineering to extract relevant information for model training.
  • Train, validate, and fine-tune machine learning models using state-of-the-art techniques. Evaluate model performance and iterate on models to improve accuracy and efficiency.
  • Deploy machine learning models into production environments and integrate them into existing systems. Collaborate with software engineers to ensure seamless integration with our products.
  • Stay abreast of the latest developments in machine learning and related fields. Proactively identify opportunities to enhance existing models and propose new approaches to solve business problems.
Requirements:
  • 3+ years of hands-on, professional machine learning development experience, delivering solutions in a large scale enterprise environment
  • Experience with Public Cloud Providers such as AWS and Microsoft Azure
  • Experience with AWS and/or Azure data tools and services
  • Demonstrated experience using AI-assisted development tools (e.g., Claude Code, Codex, GitHub Copilot) to increase development velocity, improve code quality, and support complex problem-solving
  • Strong understanding of data processing, data engineering, and data visualization.
  • Experience with SQL and NoSQL databases
  • Proficient in programming languages such as Python and R
  • Familiarity with big data technologies such as Apache Spark
  • Experience with Machine Learning frameworks such as TensorFlow or PyTorch
  • Ability to work effectively in a collaborative, cross-functional team environment. Excellent communication skills and the ability to explain complex concepts to both technical and non-technical stakeholders.
  • Strong analytical and problem-solving skills. Proven ability to tackle complex problems and deliver robust machine learning solutions.
  • Prior consulting or professional services experience is a bonus
  • Education degree or certification in Computer Science, or the equivalent related work experience
 
What's in it for you?
  • Full-time salaried consultant position
  • A true stake in success. SDG is an ESOP - 100% employee owned 
  • Star Tribune Top Workplace winner the last 7 consecutive years
  • National Top Workplace in 2023, 2024 & 2025
  • Engaged teammates who care about quality solutions 
  • Challenging and rewarding work with great customers 
  • Various opportunities to give back to the community 
  • Be amongst some of the best technologists in the industry
  • Dedicated to our core values of superior customer service, exceptional employee experience, and responsible corporate citizenship
  • Opportunities to connect with other SDGer's via internal communities, committees, and events - virtually and in person
SDG is proud to offer an array of benefits for our employees including but not limited to medical, dental, and vision insurance benefits, paid time off, paid holidays, short and long-term disability, life insurance options, a monthly technology reimbursement allowance, 401k, birth and non-birth parent leave, ESOP, trainings and certifications, and company-owned cabins. Fair and equitable compensation is important to us. The salary range for this opportunity is $130,000 - $170,000. The offer may fall outside this range given factors such as skills and experience. The salary range is subject to change and may be modified at any time.
 
 
Applicants must be authorized to work for ANY employer in the United States. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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