ZipRecruiter

Log In

1

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

IMC

Machine Learning Research Lead

Chicago, IL

IMC Trading is seeking a Machine Learning Research Lead with proven experience applying ... PhD or Master's in Engineering, Math, Statistics, Computer Science, or related quantitative field ...

Referrals Only

Lead Machine Learning Engineer

Chicago, IL · On-site

$105K - $139K/yr

You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles. * You have experience with ...

previous pagenext page

Showing results 21-40

All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Lemont, IL

Scientific Machine Learning information

See Lemont, IL salary details

$14

$31

$52

How much do scientific machine learning jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for scientific machine learning in Lemont, IL is $31.73, according to ZipRecruiter salary data. Most workers in this role earn between $19.38 and $40.48 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 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 Lemont, IL? For Scientific Machine Learning jobs in Lemont, IL, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Lemont, IL look for? The top searched job categories for Scientific Machine Learning jobs in Lemont, IL are:
What cities near Lemont, IL are hiring for Scientific Machine Learning jobs? Cities near Lemont, IL with the most Scientific Machine Learning job openings:
Scientific Machine Learning jobs near you

Principal Machine Learning Architect

Stackruit Ltd.

Naperville, IL • On-site

$130 - $160/hr

Other

Posted 3 days ago

New

Job description

Principal Machine Learning Engineer About Egen

Egen is a dynamic, fast-growing company with a strong focus on data. We combine top engineering talent with advanced technology platforms like Google Cloud and Salesforce to help clients harness data for impactful insights. Our team thrives on solving tough problems, continuously innovating to achieve rapid, effective results.

Role Overview

We are seeking a Principal Machine Learning Engineer to join our Data Science team. This critical role involves developing and enhancing our MLOps platform. You’ll need a unique blend of cloud architecture expertise, AI/ML knowledge, and leadership skills to build and maintain a state-of-the-art MLOps environment.

Key Responsibilities
  • Architectural Leadership: Design and lead our MLOps platform architecture, focusing on GCP Vertex AI and Kubeflow.
  • Responsible AI Solutions: Develop solutions that ensure Responsible AI, including explainability, data drift detection, and fairness metrics, adhering to ethical AI practices.
  • Developer Experience: Enhance the MLOps platform for optimal developer experience, incorporating streamlined workflows and advanced tools.
  • Collaboration: Work with AI/ML experts across domains like Computer Vision, NLP, and synthetic data, integrating the latest advancements into the platform.
  • Reliability and Observability: Partner with the AI/ML Reliability engineering team to ensure platform reliability and observability.
  • Platform Development: Bring experience in platform teams, particularly in data and AI/ML, and expand platforms to on-premises and edge deployments.
  • Cross-functional Collaboration: Collaborate with cloud teams, data scientists, and product managers to align platform development with organizational goals.
Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.
  • 10+ years of experience in technology or data fields.
  • Proficient in Python and other programming languages.
  • Strong background in AI/ML or Data Sciences technologies and platform development.
  • Broad knowledge across technology domains (data, cloud, UI, security).
  • Excellent communication, leadership, and project management skills.
#J-18808-Ljbffr

Apply