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Machine Learning Material Science Jobs (NOW HIRING)

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 ...

If you are an experienced Machine Learning Engineer or Data Scientist looking for an exciting opportunity to work on challenging problems and deliver machine learning products, we would love to hear ...

You will work closely with data scientists, engineers, and product managers to design, develop, and deploy machine learning models and solutions that drive business value. Key Responsibilities:

Employer will accept a Master's degree in Computer Science, Machine Learning, Data Science ... Candidates are encouraged to use AI tools to enhance their resume and/or application materials.

Machine Learning Engineer Company: HeyMilo AI Location: New York, NY, USA Contract Details ... You will work closely with our data scientists, software engineers, and product managers to ...

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 ...

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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 Scientist

Machine Learning Scientist

New York Times

Manhattan, NY • On-site

$121K - $131K/yr

Other

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

The mission (https://www.nytco.com/company/mission-and-values/) of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for.

About the Role

The New York Times is a technology company committed to producing the world's most reliable and highest quality journalism. Our ability to do so relies on a talented team of expert technologists who help NYT learn from a tremendous abundance of data unique to this company.

The Algorithmic Recommendations and Audience Data Science team aims to help users discover content across the Times' website, apps and emails by applying algorithms that make use of information about our readers' behavior and our editorial judgment. We also build internal tools for the newsroom to better understand story performance and coverage trends. We are a group of machine learning scientists and data analysts that partner with teams across The New York Times. We are looking for a Machine Learning Scientist to join the team and apply machine learning methods to meet this challenge. You will report to a Lead Machine Learning Scientist, and collaborate with partners across the company.

Responsibilities:

  • You will reframe business and newsroom goals as machine learning tasks that deliver accurate predictions, relevant insights, and optimization

  • You will adapt or develop machine learning algorithms in cases when existing algorithms are insufficient, while implementing simple approaches when appropriate

  • You will implement and deploy machine learning research with robustness and reproducibility, with consideration of risks and trade-offs

  • You will turn models into data products, collaborate with engineering teams, and integrate into processes throughout The Times

  • You will communicate complex ideas in machine learning while collaborating with technical and non-technical colleagues in in engineering, analytics, product management, marketing, editorial, and executive leadership groups

  • Demonstrate support and understanding of our value of journalistic independence (https://www.nytco.com/company/mission-and-values/) and a commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

  • PhD, MS + 2 years experience, or 3+ years work experience in machine learning, statistics, computational social science, applied mathematics, or another quantitative/computational discipline

  • 2+ years experience with open source machine learning or statistical analysis tools

  • 2+ years coding experience in Python

  • 2+ years experience in SQL and manipulating large structured or unstructured datasets for analysis

Preferred Qualifications:

  • 1+ year of experience with recommendation systems, using natural language processing and small and large language models.

  • 1+ years of experience with deep learning architectures, fine-tuning, embeddings and Pytorch or Tensorflow

  • 1+ years of experience translating ambiguous business questions into machine learning problems

  • 1+ years of experience building data products, either internal or consumer-facing

REQ-020029

The annual base pay range for this role is between:

$121,000 — $131,000 USD

For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. Benefits may include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs.

For roles outside of the U.S., information on benefits will be provided during the interview process.

The New York Times Company is committed to being the world’s best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply.

We are an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics. The U.S. Equal Employment Opportunity Commission (EEOC)’s Know Your Rights Poster is available here (https://www.eeoc.gov/know-your-rights-workplace-discrimination-illegal) .

The New York Times Company will provide reasonable accommodations as required by applicable federal, state, and/or local laws. Individuals seeking an accommodation for the application or interview process should email reasonable.accommodations@nytimes.com. Emails sent for unrelated issues, such as following up on an application, will not receive a response.

The Company encourages those with criminal histories to apply, and will consider their applications in a manner consistent with applicable "Fair Chance" laws, including but not limited to the NYC Fair Chance Act, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.

For information about The New York Times' privacy practices for job applicants click here (https://nytco-assets.nytimes.com/2020/06/NYT_Applicant_Privacy_Policy.pdf) .

Please beware of fraudulent job postings. Scammers may post fraudulent job opportunities, and they may even make fraudulent employment offers. This is done by bad actors to collect personal information and money from victims. All legitimate job opportunities from The New York Times will be accessible through The New York Times careers site (https://www.nytco.com/careers/) . The New York Times will not ask job applicants for financial information or for payment, and will not refer you to a third party to do so. You should never send money to anyone who suggests they can provide employment with The New York Times.

If you see a fake or fraudulent job posting, or if you suspect you have received a fraudulent offer, you can report it to The New York Times at NYTapplicants@nytimes.com. You can also file a report with the Federal Trade Commission (https://reportfraud.ftc.gov/#/) or your state attorney general (https://www.consumerresources.org/file-a-complaint/) .