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Scientific Machine Learning Jobs in Niles, IL (NOW HIRING)

Machine Learning Engineer

Chicago, IL · On-site

$100 - $125/hr

Advanced degree in a Science, Technology, Engineering, or Mathematics field required * Typically requires a minimum of two years of hands‑on industry experience in machine learning, computer vision ...

Machine Learning Engineer

Chicago, IL · On-site

$95K - $138K/yr

Advanced degree in a Science, Technology, Engineering, or Mathematics field required * Typically requires a minimum of two years of hands-on industry experience in machine learning, computer vision ...

We are seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional ... Partner closely with Data Scientists to support traditional ML model development, including feature ...

Oversee teams of data scientists, modelers, and ML engineers to deliver innovative and scalable ... Strategic Leadership and Vision Provide strategic direction for the organization's machine learning ...

Oversee teams of data scientists, modelers, and ML engineers to deliver innovative and scalable ... Strategic Leadership and Vision Provide strategic direction for the organization's machine learning ...

We are seeking a Staff Machine Learning Engineer / Data Scientist to serve as a technical anchor for our machine learning and AI capabilities. Reporting directly to the Director of Recommendation ...

We are seeking a Staff Machine Learning Engineer / Data Scientist to serve as a technical anchor for our machine learning and AI capabilities. Reporting directly to the Director of Recommendation ...

We are seeking a Staff Machine Learning Engineer / Data Scientist to serve as a technical anchor for our machine learning and AI capabilities. Reporting directly to the Director of Recommendation ...

Machine Learning Tutor

Wheaton, IL · 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 ...

Machine Learning Tutor

Chicago, IL · 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 ...

Machine Learning Tutor

Skokie, IL · 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 ...

... 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 ...

... 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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Scientific Machine Learning information

See Niles, IL salary details

$13

$31

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How much do scientific machine learning jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for scientific machine learning in Niles, IL is $31.33, according to ZipRecruiter salary data. Most workers in this role earn between $19.13 and $39.95 per hour, depending on experience, location, and employer.

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 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 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 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 job categories do people searching Scientific Machine Learning jobs in Niles, IL look for?

The top searched job categories for Scientific Machine Learning jobs in Niles, IL are:

What cities near Niles, IL are hiring for Scientific Machine Learning jobs?

Cities near Niles, IL with the most Scientific Machine Learning job openings:

Infographic showing various Scientific Machine Learning job openings in Niles, IL as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $65,166 per year, or $31.3 per hour.

Machine Learning Engineer

Moody

Chicago, IL • On-site

$100 - $125/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago


Job description

Let's begin! Machine Learning Engineer (14907)

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.


Employment eligibility to work in the U.S. is required, as Moody’s will not pursue visa sponsorship for this position


Skills and Competencies



  • Expertise in Python programming, including machine learning libraries such as NumPy, Pandas, and PyTorch

  • Experience with machine learning operations practices, including continuous integration and continuous deployment pipelines, model monitoring, and model maintenance preferred

  • Expertise with modern machine learning tools and platforms, including Jupyter, Docker, Git, and cloud computing environments such as Amazon Web Services or Google Cloud Platform

  • Experience building data tools for extract, transform, and load processes, extracting data from SQL and NoSQL databases, and conducting advanced data analysis

  • Experience with geographic information systems preferred

  • Excellent written and verbal communication skills, with the ability to understand and articulate business requirements and objectives to both technical and non-technical stakeholders

  • Expertise in supervised and unsupervised machine learning algorithms and their implementations, including advanced concepts such as active learning, computer vision, and deployments in complex environments

  • Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization


Education



  • Advanced degree in a Science, Technology, Engineering, or Mathematics field required

  • Typically requires a minimum of two years of hands‑on industry experience in machine learning, computer vision, data science, or a related field


Responsibilities


Develop practical, scalable, and robust machine learning and computer vision solutions that enhance product capabilities and deliver value to clients.



  • Collect, clean, preprocess, and analyze data to support machine learning model development and maximize data value

  • Create visualizations and conduct exploratory analysis to identify patterns, trends, opportunities, and data quality issues

  • Train, evaluate, refine, and deploy machine learning models aligned with business objectives and product requirements

  • Design, implement, and automate large-scale model training, integration, and evaluation pipelines

  • Collaborate with machine learning, software engineering, product development, sales, and cross-functional stakeholders to deliver innovative solutions

  • Communicate technical findings and recommendations to both technical and non-technical audiences through clear documentation and presentations

  • Design and execute experiments to validate assumptions, improve model performance, and support data-driven decision making

  • Ensure projects follow governance, security, ethical AI, and responsible data use practices while identifying and resolving operational inefficiencies


About the Team


Our Machine Learning Technology team is responsible for the core technology behind award-winning property intelligence solutions. We leverage machine learning, geospatial imagery, and computer vision to measure and monitor the built environment while delivering actionable insights to clients. By joining our team, you will contribute to innovative work that helps organizations better understand how homes and workplaces can withstand evolving climate and economic risks, while advancing the responsible adoption of artificial intelligence across our products and solutions.


For US-based roles only: the anticipated hiring base salary range for this position is$95,500.00-$138,550.00, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role is eligible for incentive compensation. Moody’s also offers a competitive benefits package, including not but limited to medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement.


Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion or creed, national origin, ancestry, citizenship, marital or familial status,sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, military or veteran status, or any other characteristic protected by law. Moody’s also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws. If you need to inquire about a reasonable accommodation, or need assistance with completing the application process, please email accommodations@moodys.com . This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications


For San Francisco positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the San Francisco Fair Chance Ordinance.


This position may be considered a promotional opportunity, pursuant to the Colorado Equal Pay for Equal Work Act.


Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.

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