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Scientific Machine Learning Jobs (NOW HIRING)

Rule14

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Data Scientist Machine Learning

Santa Monica, CA · On-site

$65K - $85K/yr

As a Data Scientist Machine Learning, you will work within a small data science team focusing on predictive modeling, natural language processing, computer vision, recommender systems, and OCR ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88.50K - $121K/yr

This role blends scientific machine learning (surrogate modeling) with sequential decision-making under uncertainty. A successful candidate will: Explore: you're open-minded about methods and will ...

Zanskar

Senior Machine Learning Scientist

Salt Lake City, UT · On-site +1

$88.50K - $121K/yr

This role blends scientific machine learning (surrogate modeling) with sequential decision-making under uncertainty. A successful candidate will: Explore: you're open-minded about methods and will ...

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... Design and implement complex data engineering processes to support innovative data science modeling

Calendly

Machine Learning Engineer

You will report to the head of Data Science & Machine Learning and will be responsible for building and operating ML-powered features that create magical experiences for our customers. Our team:

Nanite Inc.

Machine Learning Engineer

Boston, MA

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... Design and implement complex data engineering processes to support innovative data science modeling

Micron

Machine Learning Engineer

Boise, ID · On-site

Employer will accept a Master's degree in Computer Science, Machine Learning, Data Science, Statistics, Information Technology, or a field closely related to AI and ML and 2 years of experience in ...

Ontrac Solutions

Machine Learning Engineer

Chicago, IL · On-site

$70 - $90/hr

Bachelor's degree in Computer Science, Engineering, Data Science, Machine Learning, or equivalent practical experience. Required Qualifications * Solid hands-on experience with the GCP ecosystem ...

Micron Technology

Machine Learning Engineer

Boise, ID · On-site

Employer will accept a Master's degree in Computer Science, Machine Learning, Data Science, Statistics, Information Technology, or a field closely related to AI and ML and 2 years of experience in ...

Apple

Machine Learning FEA Engineer

Bodega Bay, CA

$139.50K - $258.10K/yr

D. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline Publications in top journals or conferences Minimum Qualifications Strong Expertise in Machine Learning, Deep ...

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Scientific Machine Learning information

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$13

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How much do scientific machine learning jobs pay per hour?

As of May 31, 2026, the average hourly pay for scientific machine learning in the United States is $31.48, according to ZipRecruiter salary data. Most workers in this role earn between $19.23 and $40.14 per hour, depending on experience, location, and employer.

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 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 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.

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What states have the most Scientific Machine Learning jobs? States with the most job openings for Scientific Machine Learning jobs include:
What job categories do people searching Scientific Machine Learning jobs look for? The top searched job categories for Scientific Machine Learning jobs are:
Scientific Machine Learning jobs near you
Data Scientist Machine Learning

Data Scientist Machine Learning

Rule14

Santa Monica, CA • On-site

$65K - $85K/yr

Full-time

Medical

Posted 22 days ago

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Job description

As a Data Scientist Machine Learning, you will work within a small data science team focusing on predictive modeling, natural language processing, computer vision, recommender systems, and OCR projects. You will be responsible for the end-to-end development and deployment of machine learning models, collaborating closely with cross-functional teams to deliver impactful solutions.

Responsibilities

  • Develop and train machine learning models for various applications
  • Perform feature engineering to enhance model performance
  • Select appropriate algorithms based on project requirements
  • Tune and optimize model performance for deployment
  • Clean and preprocess data to ensure model accuracy
  • Design experiments to validate and improve model outcomes
  • Collaborate within a small team to integrate machine learning solutions
  • Manage end-to-end deployment of machine learning models

Preferred Qualifications

  • Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn
  • Experience with SQL for data querying and manipulation
  • Strong skills in statistical analysis and data visualization
  • Critical thinking and effective communication abilities

Company Description

Rule14 is an AI company and technology incubator focused on applying new approaches to uncover patterns and extract valuable intelligence within big data.
Whether helping businesses gain insight on customer loss prevention, designing targeted revenue enhancement campaigns, or uncovering fraud, waste and abuse within government programs, Rule14 empowers organizations assessing massive amounts of data for real-time decision-making.
Nventr.ai focuses on applying artificial intelligence to real-world operational environments where reliability, speed, and accuracy are critical. The company builds systems that integrate AI directly into day-to-day workflows, enabling better decision-making, automation, and coordination between software and physical operations.
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About Rule14

Sourced by ZipRecruiter

Industry

Software development

Company size

11 - 50 Employees

Headquarters location

Santa Monica, CA, US

Year founded

2011

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