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Internship Machine Learning Chemistry Jobs (NOW HIRING)

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... Collaborate with chemistry and biology research teams to design data pipelines, analyze ...

Nanite Inc.

Machine Learning Engineer

Boston, MA

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... Collaborate with chemistry and biology research teams to design data pipelines, analyze ...

EarnIn

Machine Learning Intern

Mountain View, CA · Hybrid

$40/hr

This internship will pay $40 per hour, with an expected 40 hours per week for the 12-week program ... of machine learning and deep learning algorithms. Familiarity with training or fine-tuning large ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Coupang

Machine Learning Intern

Mountain View, CA · On-site

$40 - $45/hr

What you will do In this internship, you will gain hands-on experience building large-scale machine learning models for Ads retrieval and ranking. Additionally, you will have the opportunity to ...

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Internship Machine Learning Chemistry information

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$25.5K

$42.6K

$88K

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

As of May 29, 2026, the average yearly pay for internship machine learning chemistry in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship Machine Learning Chemistry, and why are they important?

To thrive as an intern in Machine Learning Chemistry, you need a solid understanding of chemistry fundamentals and proficiency in programming languages such as Python, often supported by ongoing or completed coursework in chemistry, computer science, or related fields. Familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow), cheminformatics tools (e.g., RDKit), and data analysis platforms is highly valued. Strong analytical thinking, problem-solving skills, and teamwork set standout candidates apart in collaborative research environments. These skills are important to effectively develop, implement, and interpret machine learning models that address complex chemical problems.

What are some common challenges faced during a Machine Learning Chemistry internship, and how can interns overcome them?

Interns in Machine Learning Chemistry often encounter challenges such as bridging the gap between computational methods and chemical domain knowledge, working with complex and sometimes limited datasets, and adapting to rapidly evolving technologies. To overcome these hurdles, it's helpful to proactively seek mentorship from both data scientists and chemists within the team, dedicate time to learning domain-specific concepts, and regularly participate in team discussions to clarify project goals. Embracing a collaborative mindset and staying curious will also help interns effectively contribute and grow in this interdisciplinary environment.

What is an Internship in Machine Learning Chemistry?

An Internship in Machine Learning Chemistry is a temporary, often academic or industry-based position where students or early-career professionals gain hands-on experience applying machine learning techniques to solve problems in chemistry. Interns may work on projects involving data analysis, molecular modeling, drug discovery, or material design using algorithms and computational tools. The internship provides practical exposure to interdisciplinary research, allowing interns to collaborate with chemists, data scientists, and engineers. It is an excellent opportunity to develop both technical and professional skills in a rapidly growing field.

What is the difference between Internship Machine Learning Chemistry vs Chemistry Research Intern?

AspectInternship Machine Learning ChemistryChemistry Research Intern
Required CredentialsBasic programming, chemistry knowledge, courseworkChemistry coursework, lab skills, basic research experience
Work EnvironmentData analysis, coding, computational toolsLaboratory experiments, chemical analysis
Industry UsageTech companies, research labs integrating ML and chemistryAcademic, industrial chemistry labs
Search & Comparison IntentUnderstanding roles combining ML and chemistry internshipsTraditional chemistry research internship details

Internship Machine Learning Chemistry focuses on applying machine learning techniques to chemistry problems, often involving coding and data analysis. In contrast, Chemistry Research Internships emphasize hands-on laboratory research in chemistry. Both roles require chemistry knowledge, but the former integrates computational skills, making it ideal for those interested in data-driven chemistry careers.

More about Internship Machine Learning Chemistry jobs
What cities are hiring for Internship Machine Learning Chemistry jobs? Cities with the most Internship Machine Learning Chemistry job openings:
What are the most commonly searched types of Machine Learning Chemistry jobs? The most popular types of Machine Learning Chemistry jobs are:
What states have the most Internship Machine Learning Chemistry jobs? States with the most job openings for Internship Machine Learning Chemistry jobs include:
What job categories do people searching Internship Machine Learning Chemistry jobs look for? The top searched job categories for Internship Machine Learning Chemistry jobs are:
Internship Machine Learning Chemistry jobs near you
Infographic showing various Internship Machine Learning Chemistry job openings in the United States as of May 2026, with employment types broken down into 78% Full Time, 11% Part Time, 7% Contract, and 4% Nights. Highlights an 69% Physical, 4% Hybrid, and 27% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer

Nanite Inc.

Boston, MA • On-site

Full-time

Posted 20 days ago

Job description

Our mission is to deliver the undeliverable.
Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug delivery. The research intern will be in a fast-paced start-up environment playing a crucial technical role in generating cell culture and transfection data. The candidate will work with senior leadership and partner projects gaining broad internal and external exposure.
Essential Functions and Duties
  • Design and implement complex data engineering processes to support innovative data science modeling
  • Collaborate with chemistry and biology research teams to design data pipelines, analyze experimental data and implement experimentally actionable feed-back loops
  • Apply and deploy established and novel statistical and machine learning algorithms to explore, understand and optimize properties of the vast delivery vehicle space, both in silico and experimentally
  • Develop robust, scalable workflows and maintain security controls to protect sensitive data across cloud and on-premise environments
  • Coordinate with cross-functional teams to deploy models and communicate results and with a focus on computational efficiency, performance, and usability
  • Design of repositories, CI/CD pipelines and integration tests for ML workflows

Qualifications
MS in Computer Science, Data Science, Statistics, Computational Biology, Computational Chemistry, or a related discipline with 2 years hands-on machine learning experience.
Knowledge, Skills, and Abilities
  • Track record developing statistical and machine learning models for complex and unconventional real-life problems
  • Strong mathematical and coding skills
  • Proficiency in Python, MLOps (W&B, MLFlow) and ML packages (scikit-learn, PyTorch, JAX), along with SQL and AWS.
  • Familiarity with ML workflow best practices.
  • Interest in applications of machine learning in biotechnology
  • Strong communication skills, both written and verbal
  • Experience doing research and working with interdisciplinary teams

Additional Preferred Experience (desired, but not essential):
  • Experience in an industry setting related to biotechnology, chemicals, or materials manufacturing
  • Experience with cheminformatics, computational chemistry, computational biology databases, data structures, material science and modelling package

Computer and modeling work required, this is an on-site position based in the Seaport of Boston, MA.

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