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Materials Science Python Jobs (NOW HIRING)

Formlabs

Materials Scientist

Somerville, MA

... science or engineering field (all are welcome) Bonus Skills: * Experience developing materials for 3D printing, especially for SLA/DLP or SLS printers! * 3D CAD modeling * Programming skills (Python ...

Formlabs

Materials Scientist

Boston, MA

... science or engineering field (all are welcome) Bonus Skills: * Experience developing materials for 3D printing, especially for SLA/DLP or SLS printers! * 3D CAD modeling * Programming skills (Python ...

Formlabs

Materials Scientist

Somerville, MA · On-site

$75K - $115K/yr

... science or engineering field (all are welcome) Bonus Skills: * Experience developing materials for 3D printing, especially for SLA/DLP or SLS printers! * 3D CAD modeling * Programming skills (Python ...

Formlabs

Materials Scientist

Boston, MA · On-site

$75K - $115K/yr

... science or engineering field (all are welcome) Bonus Skills: * Experience developing materials for 3D printing, especially for SLA/DLP or SLS printers! * 3D CAD modeling * Programming skills (Python ...

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How much do materials science python jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for materials science python in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Materials Science Python Specialist, and why are they important?

To thrive as a Materials Science Python Specialist, you need a solid background in materials science principles and strong proficiency in Python programming, often supported by a relevant degree in materials science, engineering, or a related field. Familiarity with technical tools such as NumPy, pandas, Matplotlib, and materials modeling software (e.g., LAMMPS, VASP), as well as version control systems like Git, is essential. Analytical thinking, problem-solving skills, and effective communication set standout professionals apart in this role. These skills ensure accurate data analysis, efficient computational modeling, and successful collaboration across interdisciplinary teams in research and development settings.

How does a Materials Science Python specialist typically collaborate with cross-functional teams in research and development projects?

Materials Science Python specialists often work closely with researchers, experimentalists, and engineers to develop and implement computational models for materials analysis. They are responsible for writing scripts to automate data processing, simulate material properties, and visualize complex results, ensuring that findings are accessible and actionable for the entire team. Effective collaboration requires regular communication to translate experimental needs into computational tasks, share code and results, and refine methodologies based on feedback. This cross-disciplinary interaction is key to accelerating innovation and achieving project goals.

What is a Materials Science Python professional?

A Materials Science Python professional is someone who utilizes the Python programming language to analyze, model, and simulate materials science data and processes. They often work on tasks such as computational materials modeling, data analysis, visualization, and automation of laboratory or simulation workflows. These professionals bridge the gap between materials science and computer programming, enabling more efficient research and development of new materials. Their work can involve using specialized Python libraries like NumPy, Pandas, Matplotlib, and domain-specific tools such as pymatgen or ASE (Atomic Simulation Environment).

What is the difference between Materials Science Python vs Materials Engineer?

AspectMaterials Science PythonMaterials Engineer
Required CredentialsPython programming skills, knowledge of materials scienceBachelor's or Master's in Materials Science or Engineering
Work EnvironmentResearch labs, software development, data analysisManufacturing, product development, testing facilities
Industry UsageData modeling, simulations, automation in materials researchDesigning, testing, and improving materials for products

Materials Science Python professionals focus on coding, data analysis, and simulations using Python, often working in research or software roles. Materials Engineers apply their knowledge directly to product development and manufacturing processes. While both roles require understanding of materials, Python skills are central for the former, whereas hands-on engineering is key for the latter.

Infographic showing various Materials Science Python job openings in the United States as of May 2026, with employment types broken down into 79% Full Time, 5% Part Time, 11% Contract, and 5% Nights. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution, with an average salary of $121,932 per year, or $58.6 per hour.
Materials Science Ai Engineer

Materials Science Ai Engineer

Cardinal Integrated

Santa Clara, CA • Hybrid

Other

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

Job description

Materials Science AI Engineer

Location: Santa Clara, CA - 5D Onsite Duration: 6-12+ Months Contract

Must Have Skills:

  • Strong proficiency in programming languages like Python and C++.
  • Experience with machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow).
  • Experience with data cleansing, preprocessing, and feature engineering.

Good To Have Skills:

  • Design, develop and deploy multi-modal AI, ML, and hybrid physical-based models to solve ground-breaking material physics and design problems.

We are seeking an AI Scientist/Engineer to join our team in developing and supporting materials discovery and design. The ideal candidate will have strong experience building AI-based solutions for building neural network architecture, attention mechanisms, multi-modal learning, aggregating and structuring training data, statistical theory, and cloud-based compute for parallelized, scalable, and automated workflows.

Key Responsibilities:

  • Design, develop and deploy multi-modal AI, ML, and hybrid physical-based models to solve ground-breaking material physics and design problems.
  • Aggregate, process, transform and quality-control experimental and simulation data for modeling and analysis.
  • Design, develop, and maintain data workflows to support materials informatics initiatives. Optimize data pipelines and model execution on parallel cloud systems (e.g., Azure, GCP, AWS).
  • Collaborate with materials scientists, chemists, and software engineers to integrate analytics and predictive modeling into core R&D workflows.
  • Document code, workflows, and best practices to support reproducible research.
  • Apply AI and data analytics to optimize material synthesis and processing parameters in real-time, minimizing defects, improving consistency.

Technical Skills:

  • Strong proficiency in programming languages like Python and C++.
  • Experience with machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow).
  • Knowledge of generative modeling techniques and architectures (e.g., GANs, VAEs, transformers).
  • Knowledge of MLOps, model deployment pipelines, and CI/CD.
  • Experience with data cleansing, preprocessing, and feature engineering.

Qualifications:

  • Graduate or undergraduate degree in Computer Science, Engineering, Applied Mathematics, or a related technical field.
  • 2-4 years of work experience (depending on educational degree) in data science, AI, machine learning, or data engineering roles.
  • A strong foundation in the principles of materials science is essential to understand the underlying science and set up meaningful problems for AI.
  • Expert in Python and data science libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow or PyTorch).
  • Expertise in use of cloud-based compute environments and tools for parallel or distributed computing.
  • Strong problem-solving and communication skills.

Apply