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Scientific Machine Learning Jobs in Ohio (NOW HIRING)

Flexjet LLC

Machine Learning Engineer

Cleveland, OH · On-site

$60 - $80/hr

In this role, you will work alongside experienced engineers and data scientists to build, deploy, and maintain machine learning models. This is an excellent opportunity for someone early in their ...

Flexjet

Machine Learning Engineer

Cleveland, OH · On-site

In this role, you will work alongside experienced engineers and data scientists to build, deploy, and maintain machine learning models. This is an excellent opportunity for someone early in their ...

Flexjet

Machine Learning Engineer

Cleveland, OH · On-site

In this role, you will work alongside experienced engineers and data scientists to build, deploy, and maintain machine learning models. This is an excellent opportunity for someone early in their ...

Flexjet

Machine Learning Engineer

Cleveland, OH

In this role, you will work alongside experienced engineers and data scientists to build, deploy, and maintain machine learning models. This is an excellent opportunity for someone early in their ...

elobau GmbH

$250/hr

Du studierst Informatik, Data Science, Wirtschaftsinformatik oder einen vergleichbaren Studiengang ... Machine Learning.* Du hast ein grundlegendes Verständnis für Datenanalyse und Modellierung und ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

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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 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 are popular job titles related to Scientific Machine Learning jobs in Ohio?

For Scientific Machine Learning jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in Ohio look for?

The top searched job categories for Scientific Machine Learning jobs in Ohio are:

What cities in Ohio are hiring for Scientific Machine Learning jobs?

Cities in Ohio with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Ohio as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 21% Part Time, 3% Contract, and 1% Nights. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.

Machine Learning Engineer

Cleveland, OH • On-site

Flexjet LLC
Aerospace Product and Parts Manufacturing • 501 - 1,000 employees
Learn more about Flexjet LLCexternal

$60 - $80/hr

Other

Re-posted 4 days ago

Flexjet rating

7.8

Company rating: 7.8 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

22nd of 68 rated aviation services

Job description

Current job opportunities are posted here as they become available.


Flexjet is seeking a motivated Entry-Level Machine Learning Engineer to join our team. In this role, you will work alongside experienced engineers and data scientists to build, deploy, and maintain machine learning models. This is an excellent opportunity for someone early in their career who is eager to develop hands-on experience with real-world ML systems.


DUTIES & RESPONSIBILITIES

  • Assist in developing and training machine learning models

  • Support the creation and maintenance of data pipelines

  • Help deploy ML models into production under guidance

  • Clean, preprocess, and analyze datasets for model training

  • Collaborate with team members to solve business problems using data

  • Monitor model performance and help troubleshoot issues

  • Document code, processes, and model behavior


REQUIRED SKILLS & QUALIFICATIONS

  • Bachelor's degree in Computer Science, Data Science, Engineering, or related field (or equivalent practical experience)

  • Basic proficiency in Python

  • Familiarity with machine learning concepts (regression, classification, clustering)

  • Experience with libraries such as scikit-learn, TensorFlow, or PyTorch (academic or project-based)

  • Understanding of data structures and algorithms fundamentals

  • Basic knowledge of SQL and data handling


PREFERRED QUALIFICATIONS

  • Internship, academic project, or personal project experience in machine learning

  • Familiarity with Git and version control

  • Exposure to cloud platforms (AWS, Azure, or Google Cloud)

  • Basic understanding of APIs or web services

  • Experience with data visualization tools (e.g., Matplotlib, Seaborn)

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