ZipRecruiter

Log In

1

Scientific Machine Learning Jobs (NOW HIRING)

Chabez Tech

Machine Learning Engineer

Portland, OR · On-site

... computer science, Machine Learning, Electrical Engineering, or related field • 5+ years of ... experience in machine learning, data science, or AI engineering • Strong programming skills in ...

Apple

Machine Learning FEA Engineer

San Francisco, CA · On-site

S. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline along with 3+ years of relevant experience Preferred Qualifications Strong expertise in GNNs, CNNs, and ...

Spotify

Machine Learning Engineer

... scientists, machine learning engineers, and data engineers • Experience in optimizing machine learning models for production use cases • Familiarity with creating model success metric dashboards ...

Spotify

Machine Learning Engineer

... scientists, machine learning engineers, and data engineers • Experience in optimizing machine learning models for production use cases • Familiarity with creating model success metric dashboards ...

Rule14

Data Scientist Machine Learning

Santa Monica, CA · On-site

$75K - $100K/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 ...

Atoms

Machine Learning Engineer

Mountain View, CA · On-site

... Computer Science, Machine Learning, Data Mining, Statistics, or related technical field with ... preferred 3+ years of relevant experience Company : Atoms is a design company that specializes in ...

Atoms

Machine Learning Engineer

Mountain View, CA · On-site

... Computer Science, Machine Learning, Data Mining, Statistics, or related technical field with ... preferred 3+ years of relevant experience Company : Atoms is a robotics startup that develops ...

HCLTech

Machine Learning Engineer

Plano, TX · On-site

HCLTech is looking for an experienced AI/ML Engineer / Data Scientist to design, develop, and deploy advanced machine learning and data science solutions. The ideal candidate will have expertise in ...

Genentech

Machine Learning Engineer

South San Francisco, CA · On-site +1

$168K - $312K/yr

The Machine Learning Engineer sits on the Data Science & Machine Learning Team to help the CMG (Commercial, Medical and Government) organization achieve its vision by unlocking value from data ...

New

Stefanini

Machine Learning Engineer

Allen Park, MI · On-site

... science methodologies including Machine Learning (ML), predictive modeling, math, statistics, advanced analytics, etc. Key ResponsibilitiesUnderstand business requirements and analyze datasets to ...

next page

Showing results 1-20

All JobsScientific Machine Learning Jobs

Scientific Machine Learning information

See salary details

$13

$31

$52

How much do scientific machine learning jobs pay per hour?

As of Jul 11, 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 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 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 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 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.

More about Scientific Machine Learning jobs
What cities are hiring for Scientific Machine Learning jobs? Cities with the most Scientific Machine Learning job openings:
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
Infographic showing various Scientific Machine Learning job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $65,473 per year, or $31.5 per hour.
Scientist, Machine Learning

Scientist, Machine Learning

Atomic AI

South San Francisco, CA • On-site

$170K - $220K/yr

Other

Re-posted 13 days ago

Job description

At Atomic AI, we build artificial intelligence to pioneer new frontiers in drug discovery. Our unique R&D platform, an early version of which was featured on the cover of Science, provides new strategies to treat previously undruggable diseases by targeting RNA. We continue to advance this platform by developing new machine learning methods and unique foundation models fueled by our large-scale, in-house experimental data collection. We are an interdisciplinary team of scientists and engineers and believe our people are our greatest strength and the key to our success.

The opportunity

As a full-time Scientist on the Machine Learning team, you will work closely with engineers and experimental scientists to advance our technology platform for RNA structure prediction, target identification, and early drug discovery. You will co-lead the development and evaluation of the machine learning pipeline. You will contribute new ideas and realize their potential as part of a continuously advancing state-of-the-art platform. You will proactively shape the directions of the machine learning efforts and those of the whole company. 

Primary responsibilities

  • Design and develop novel machine learning models for RNA structure prediction and drug targeting.
  • Evaluate and advance the state of the art of our structure prediction platform.
  • Collaborate with our wetlab team on the targeted acquisition of experimental data to improve our machine learning models.
  • Develop high-quality code in a team setting.
  • Analyze, interpret, and organize results and present progress to colleagues in regular research meetings.
  • Work within a collaborative, high-caliber, interdisciplinary team and proactively shape the scientific and strategic vision of the company.

About you

  • Ph.D., M.Sc., or M.Eng. in Computer Science, Physics, Applied Mathematics, Materials Science, Computational Biology, or related field.
  • 4+ years of experience developing machine learning methods for scientific applications.
  • Foundational knowledge of machine learning and underlying mathematical concepts.
  • Proficiency in Python and deep learning frameworks (e.g., JAX, PyTorch).
  • Excellent presentation and writing skills, able to clearly communicate technical information to colleagues.

Pluses

  • Publications at major machine learning conferences or in major scientific journal
  • Research experience related to structural biology, molecular design, and drug discovery.
  • Foundational knowledge of physics, chemistry, and molecular biology.
  • Demonstrated ability to develop performant code.

Salary Range (all levels): $170,000/year to $220,000/year + equity + benefits. This range reflects variations in seniority, expertise, and skills.

Atomic AI logo

About Atomic AI

Sourced by ZipRecruiter

Industry

Biotechnology research and development

Company size

11 - 50 Employees

Headquarters location

South San Francisco, CA, US

Year founded

2021

Social media

Twitter

View All Atomic AI Jobs

Apply