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Machine Learning Material Science Jobs (NOW HIRING)

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background ... Experience working with scientific or time-series datasets, especially in battery, materials, or ...

Demoind

Machine Learning

California, PA · On-site

D. (with 0 - 2 years of experience) in a relevant field such as Probability, Statistics, Machine Learning, Data Mining, Artificial intelligence Computer Science. - Experience with building data ...

Gotion

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Fremont, California Gotion Inc. is based in Silicon Valley, CA, currently ... Experience working with scientific or time-series datasets, especially in battery, materials, or ...

The New York Times

Machine Learning Scientist

New York, NY · On-site

$121K - $131K/yr

The Algorithmic Recommendations and Audience Data Science team aims to help users discover content ... We are a group of machine learning scientists and data analysts that partner with teams across The ...

The New York Times

Machine Learning Scientist

Manhattan, NY · On-site

$121K - $131K/yr

The Algorithmic Recommendations and Audience Data Science team aims to help users discover content ... We are a group of machine learning scientists and data analysts that partner with teams across The ...

Forhyre

Machine Learning Engineer

New York, NY

Study and transform data science prototypes * Design machine learning systems * Research and ... implement appropriate ML algorithms and tools * Develop machine learning applications according to ...

Dark Wolf

Machine Learning Engineer

Herndon, VA · On-site

Required : • Master's in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science ...

EarnIn

Machine Learning Intern

Mountain View, CA · Hybrid

$40/hr

Actively pursuing a Master's or PhD in Computer Science, Information Technology, or a related field ... of machine learning and deep learning algorithms. Familiarity with training or fine-tuning large ...

SysMind Tech

Machine Learning

Manhattan, NY · On-site

$85/hr

Stay updated with the latest trends and technologies in data science and machine learning. Basic Qualifications: Proficient in Python, Pandas, NumPy, Scikit-Learn, PySpark Bachelor s degree in ...

Dark Wolf

Machine Learning Engineer

Chantilly, VA · On-site

Required : • Master's in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science ...

1872 Consulting

Machine Learning Engineer

Reston, VA · On-site

You will be working closely with our Data Scientists, implementing highly available and scalable machine learning pipelines. If you are a Software Engineer passionate for technology who wants to work ...

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Machine Learning Material Science information

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

To thrive as a Machine Learning Material Scientist, you need a strong background in materials science, mathematics, and machine learning, often supported by an advanced degree in a related field. Proficiency with programming languages like Python, data analysis tools, and machine learning frameworks such as TensorFlow or scikit-learn is typically required. Strong problem-solving abilities, effective communication, and collaborative skills are essential for interdisciplinary teamwork and conveying complex findings. These skills are crucial for developing innovative materials solutions and accelerating research and development through data-driven approaches.

How do professionals in machine learning material science typically collaborate with experimental scientists and engineers?

In machine learning material science, collaboration with experimental scientists and engineers is essential. Professionals in this role often work closely with lab teams to understand experimental data, design new experiments, and validate machine learning predictions. Regular meetings, shared databases, and interdisciplinary project teams are common, allowing for feedback and integration of computational results with physical testing. This collaborative environment ensures that machine learning models are grounded in real-world data and that discoveries can be rapidly prototyped and tested.

What is a Machine Learning Material Scientist?

A Machine Learning Material Scientist is a professional who combines expertise in materials science with advanced knowledge of machine learning techniques. They use algorithms and data-driven models to analyze, predict, and design materials with desirable properties for various applications. This interdisciplinary role often involves processing large datasets, developing predictive models, and collaborating with experimentalists to accelerate materials discovery and optimization.

What is the difference between Machine Learning Material Science vs Materials Engineer?

AspectMachine Learning Material ScienceMaterials Engineer
Required CredentialsMaster's or PhD in Data Science, Materials Science, or related fieldsBachelor's or Master's in Materials Engineering or related disciplines
Work EnvironmentResearch labs, tech companies, academia focusing on data-driven modelingManufacturing plants, R&D labs, construction sites
Industry UsageDeveloping algorithms to predict material properties, optimizing material designDesigning, testing, and implementing new materials for products and structures

Machine Learning Material Science focuses on applying data science and machine learning techniques to understand and predict material behaviors, while Materials Engineers work on designing, testing, and developing new materials through traditional engineering methods. Both roles are essential in advancing material innovation but differ in their approach and skill sets.

Infographic showing various Machine Learning Material Science job openings in the United States as of May 2026, with employment types broken down into 87% Full Time, 8% Part Time, 3% Temporary, 1% Contract, and 1% Nights. Highlights an 75% Physical, 1% Hybrid, and 24% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Gotion, Inc.

Fremont, CA • On-site

Other

Posted 25 days ago

Job description

About The Team
The Product Development Team at Gotion Illinois New Energy Inc. focuses on the design and development of advanced battery products for next-generation energy storage system (ESS) and electric vehicle (EV) applications. We lead the full product development cycle, integrating mechanical, electrical, thermal, and control system to create high-performance battery solutions, along with comprehensive system integration, validation, and certification activities.

Role Summary

We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains such as battery technology, energy systems, or related physical sciences. This is a fully on-site role based in Manteno, IL focused on building innovative ML models from the ground up.

You will collaborate closely with cross-disciplinary R&D teams to develop and deploy machine learning solutions that address real-world challenges in advanced materials, electrochemical systems, and high-throughput data environments.

Essential Duties and Responsibilities:

  • Design and implement novel machine learning and deep learning models tailored to internal research needs
  • Prototype and evaluate state-of-the-art algorithms, including Transformers, LLMs, and hybrid model architectures
  • Conduct rigorous experimentation, benchmarking, and ablation studies
  • Collaborate with battery scientists and domain experts to incorporate physical constraints or scientific priors into modeling
  • Contribute to internal documentation and present research outcomes to technical and leadership teams
  • Track and integrate advances from the ML research community to ensure technical excellence

Required Qualifications:

  • Ph.D. (preferred) or M.S. in Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, or a closely related field
  • Demonstrated expertise in model development, optimization, and algorithmic innovation
  • Proficiency in Python and ML libraries/frameworks such as PyTorch, TensorFlow, etc.
  • Solid understanding of learning theory concepts such as regularization, generalization, loss functions, and evaluation metrics
  • Experience working with scientific or time-series datasets, especially in battery, materials, or energy domains, is highly desirable
  • A publication record in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR) is a strong plus
  • Excellent communication, collaboration, and problem-solving skills in interdisciplinary environments

The US base salary range for this full-time position is $80,000.00 - $90,000.00 + 15% bonus + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.   

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