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Machine Learning Computational Chemistry Jobs (NOW HIRING)

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

$9.7K/wk

You will leverage in-house computational tools and contribute to the design, training, and evaluation of new machine learning-based methods. Depending on your assignment, this position may offer a ...

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Machine Learning Computational Chemistry information

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$24.5K

$114.5K

$211.5K

How much do machine learning computational chemistry jobs pay per year?

As of Jun 29, 2026, the average yearly pay for machine learning computational chemistry in the United States is $114,469.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,000.00 and $154,500.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Computational Chemistry vs Computational Chemist?

AspectMachine Learning Computational ChemistryComputational Chemist
Required CredentialsAdvanced degrees in chemistry, computer science, or related fields; knowledge of machine learning and programmingDegree in chemistry, chemical engineering, or related fields; strong background in chemical theory and modeling
Work EnvironmentResearch labs, tech companies, academia; focus on algorithm development and data analysisLaboratories, research institutions, industry; focus on chemical modeling and simulation
Employer & Industry UsageTech firms, pharmaceutical companies, research institutions applying AI/ML techniquesPharmaceutical, chemical, and materials industries conducting chemical research and development

Machine Learning Computational Chemists specialize in applying machine learning algorithms to chemical data, enhancing predictive models and simulations. Computational Chemists focus on traditional chemical modeling and simulations using computational methods. Both roles require strong chemistry backgrounds, but Machine Learning Computational Chemists emphasize data science and AI skills, while Computational Chemists focus on chemical theory and modeling techniques.

What is machine learning computational chemistry?

Machine learning computational chemistry is a field that combines machine learning techniques with computational chemistry to accelerate the discovery and design of molecules and materials. By training algorithms on large datasets of chemical information, researchers can predict molecular properties, simulate chemical reactions, and optimize compounds more efficiently than traditional methods. This approach helps reduce the time and cost required for research in drug discovery, materials science, and related fields.

What are some common challenges faced by professionals working in Machine Learning Computational Chemistry roles?

One common challenge in Machine Learning Computational Chemistry roles is integrating large and often complex chemical datasets with appropriate machine learning models, which requires a solid understanding of both domains. Professionals may also encounter difficulties in ensuring that their models are both interpretable and generalizable to new data, as overfitting is a frequent issue. Additionally, collaboration with chemists and data scientists is essential, so clear communication across disciplines is key to success. Staying up to date with the latest developments in both computational chemistry and machine learning is crucial for ongoing professional growth.

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

To thrive as a Machine Learning Computational Chemist, you need a solid background in chemistry, mathematics, and computer science, typically supported by an advanced degree in computational chemistry, cheminformatics, or a related field. Proficiency with programming languages (such as Python), machine learning frameworks (like TensorFlow or PyTorch), and molecular modeling software is essential. Strong analytical thinking, problem-solving skills, and effective collaboration are key soft skills that help drive innovation and teamwork. These skills and qualifications are critical for developing accurate models, advancing research, and translating computational insights into real-world chemical solutions.
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What cities are hiring for Machine Learning Computational Chemistry jobs? Cities with the most Machine Learning Computational Chemistry job openings:
What states have the most Machine Learning Computational Chemistry jobs? States with the most job openings for Machine Learning Computational Chemistry jobs include:
What job categories do people searching Machine Learning Computational Chemistry jobs look for? The top searched job categories for Machine Learning Computational Chemistry jobs are:
Machine Learning Computational Chemistry jobs near you
Infographic showing various Machine Learning Computational Chemistry job openings in the United States as of June 2026, with employment types broken down into 4% As Needed, 77% Full Time, 11% Part Time, 4% Contract, and 4% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $114,469 per year, or $55 per hour.
Senior HPC Performance Engineer - AI for Science at Scale

Senior HPC Performance Engineer - AI for Science at Scale

Nvidia Corporation

Santa Clara, CA • On-site

$143K - $189K/yr

Full-time

Posted 20 days ago

Key responsibilities

  • Design and implement computationally performant features for large scale, CUDA-backed machine learning training frameworks using low level acceleration and scaling strategies.

  • Optimize computational performance of a wide range of machine learning models via accelerated hardware and software stack, as well as algorithmic improvements.

  • Develop and maintain HPC software stack for atomistic modeling and generative machine learning in digital biology and beyond.

Job description

NVIDIA has become the platform upon which every new AI-powered application is built. We are seeking a Sr. HPC Performance engineer to join our team of scientists and engineers passionate about building the next generation of scientific machine learning (ML) frameworks. Starting with digital biology, through high performance computing (HPC) and powerful ML methods, together, we will advance NVIDIA's capacity to accelerate AI for Science and industries that depend on it.
What you'll be doing:
  • Design and implement computationally performant features for large scale, CUDA-backed ML training frameworks, using low level acceleration and scaling strategies such as kernel design, GPU porting, data structure innovations, distributed learning technologies
  • Optimize computational performance of wide range of business-critical ML models via accelerated hardware and software stack, as well as algorithmic improvements
  • Develop and maintain HPC software stack for atomistic modeling and generative machine learning in digital biology and beyond
  • Collaborate with multiple HPC, AI infrastructure, and research teams
  • Drive the testing and maintenance of the algorithms and software modules

What we need to see:
  • Advanced degree in a quantitative field such as Computer Science, Computational Biophysics, Computational Chemistry, Physics, Mathematics, or equivalent experience
  • 5+ years of relevant experience
  • Consistent track record in performance engineering as well as software design, building and packaging and launching software products, with a focus on acceleration
  • Deep understanding of parallel programming in C++, Python; programming experience CUDA or OAI Triton
  • Fluent in modern machine learning frameworks such as PyTorch, JAX, Warp
  • Experience with HPC solutions to research problems for biology or chemistry, including but not limited to atomistic simulations
  • Recognized for technical leadership contributions, capable of self-direction, and ability to learn from and teach others
  • You should display strong communication skills, be organized and self-motivated, and play well with others (be an excellent teammate!)

Ways to stand out from the crowd:
  • Contribution to major scientific AI for Science codebase with acceleration features such as new kernels
  • Familiarity with pioneering language and geometric models used in AI for Science applications in biology and chemistry

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We are an equal opportunity employer and value diversity at our company. We have some of the most forward-thinking, resourceful and talented people in the world working with us and our engineering teams are growing fast in some of the hottest state-of-the-art fields: Digital Biology, Artificial Intelligence, and Autonomous Vehicles. Are you a creative and autonomous engineer with a real passion for machine learning, computational chemistry, data science & parallel computing? If so, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until February 21, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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