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Phd Chemistry Machine Learning Jobs (NOW HIRING)

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

As part of our machine learning team, you will play a vital role in prototyping foundational ... MS/PhD in computer vision, electrical, optical or computer engineering or related fields.Experience ...

Bayer

Principal Machine Learning Scientist

Cambridge, MA · On-site

$123K - $185K/yr

Communicate, educate, and engage with a broad set of stakeholders (chemists, biologists ... Preferred Qualifications: 5+ years of relevant post-PhD experience, including 2+ years in industry;

SAIC

Machine Learning Developer

Arlington, VA · Hybrid

The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI ... PhD and zero (0) years related experience; four (4) years of experience considered in lieu of ...

Bayer

$123K - $185K/yr

Communicate, educate, and engage with a broad set of stakeholders (chemists, biologists ... Preferred Qualifications: 5+ years of relevant post-PhD experience, including 2+ years in industry;

SAIC

Machine Learning Developer

Arlington, VA · On-site

The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI ... PhD and zero (0) years related experience; four (4) years of experience considered in lieu of ...

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How much do phd chemistry machine learning jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for phd chemistry machine learning in the United States is $22.26, according to ZipRecruiter salary data. Most workers in this role earn between $18.27 and $24.52 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a PhD Chemistry professional specializing in Machine Learning, and why are they important?

To thrive as a PhD Chemistry professional specializing in Machine Learning, you need deep expertise in chemistry, strong programming skills (e.g., Python), and advanced knowledge of machine learning algorithms, typically supported by a doctoral degree. Familiarity with tools like TensorFlow, PyTorch, cheminformatics platforms, and statistical analysis software is commonly required. Effective problem-solving, interdisciplinary collaboration, and clear communication are vital soft skills in this field. These abilities are critical for developing innovative computational models, driving scientific discovery, and translating data-driven insights into practical chemical solutions.

What is the difference between Phd Chemistry Machine Learning vs Data Scientist?

AspectPhd Chemistry Machine LearningData Scientist
Required CredentialsPhD in Chemistry or related field, expertise in machine learningBachelor's or Master's in Data Science, Computer Science, or related field; some roles prefer PhD
Work EnvironmentResearch labs, R&D departments, academia, industry research teamsTech companies, finance, healthcare, consulting firms
Industry UsageDeveloping ML models for chemical data analysis, drug discovery, materials scienceBuilding predictive models, data analysis, business insights across sectors

While both roles involve machine learning, Phd Chemistry Machine Learning specialists focus on applying ML techniques to chemical and scientific data, often within research or industry R&D. Data Scientists have a broader scope, working across various industries to analyze data and develop models. The key difference lies in domain expertise and application focus.

How does a PhD in Chemistry with a focus on Machine Learning typically collaborate with interdisciplinary teams in industry settings?

Professionals in this role often work closely with chemists, data scientists, and software engineers to design experiments, analyze complex datasets, and develop predictive models. Effective communication is key, as you may need to translate chemical concepts into machine learning frameworks and vice versa. Regular meetings and collaborative projects are common, allowing you to contribute your chemistry expertise while learning from colleagues in computing and engineering. This interdisciplinary environment fosters innovation and can open pathways to leadership or specialized research roles.

What is a PhD in Chemistry with a focus on Machine Learning?

A PhD in Chemistry with a focus on Machine Learning is a doctoral program that combines advanced chemistry research with computational techniques from machine learning and artificial intelligence. Students in this program apply machine learning algorithms to solve complex chemical problems, such as predicting molecular properties, accelerating drug discovery, or analyzing large datasets from experiments. This interdisciplinary field prepares graduates for careers in academia, industry, or research, where they can leverage computational tools to advance chemical science.
Infographic showing various Phd Chemistry Machine Learning job openings in the United States as of May 2026, with employment types broken down into 95% Full Time, 3% Part Time, 1% Temporary, and 1% Contract. Highlights an 84% Physical, 1% Hybrid, and 15% Remote job distribution, with an average salary of $46,292 per year, or $22.3 per hour.
Machine Learning Engineer

Machine Learning Engineer

Infinite Resource Solutions

Atlanta, GA • On-site

Other

Posted 26 days ago

Job description

Job Description Machine Learning Engineer Roles and Responsibilities Lead the end-to-end architecture and development of machine learning solutions. Implement machine learning algorithms into services and pipelines to be consumed at large-scale. Engineer large scale development systems using full-stack, distributed shallow and deep-learning technologies and big data technologies.

Architect and develop a highly scalable, distributed, multi-tenant set of microservices backend solutions. Be a part of a highly productive and creative engineering team What Are We Looking For in This Role. Highly Preferred: MS or PhD in Machine learning, Computer Vision, Natural Language Processing or a related field.

5+ years of experience architecting and developing AI and machine learning applications Ability to think critically, question assumptions and devise solutions to challenging technical problems. Hands-on experience with one or more of the following technologies: --Machine Learning: TensorFlow, PyTorch, Spark ML/MLib etc. --ML Technologies: NLP, Computer Vision and related technologies.

--Back end web-services: Java, Spring Boot, Python, Kubernetes, Docker - Big Data technologies: Kafka, Apache Spark, MapR, Hbase, Hive, HDFS etc. Minimum Qualifications Bachelor's Degree Relevant Experience or Degree in: Computer Science, Management Information Systems, Business or related field Typically Minimum 6 Years Relevant Exp Four-year college degree and 6 or more years, and/or a high school diploma with 8 or more years professional experience with full life cycle design and development

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