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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 · 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 ...

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/yr

Partner with process and chemistry experts to understand the unit operations you're modeling. Desired Qualifications * 0-4 years of experience (including internships or research) in machine learning ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

Jane Street

Machine Learning Engineer

New York, NY

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

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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 Jul 9, 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 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 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 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 July 2026, with employment types broken down into 1% Internship, 1% As Needed, 79% Full Time, 16% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Internship - Machine Learning Engineer

Internship - Machine Learning Engineer

Smule

Salt Lake City, UT • Remote

Other

Re-posted 7 days ago

Job description

Salary:

Smule has been on a mission to bring the world together through music since 2008. Music is much more than listening it's about creating, sharing, discovering, participating, and connecting with people. With dozens of millions of monthly active users creating over 20 million songs every day, Smule is connecting people all over the world through the joy of making music and transforming the music landscape from one of passive listening to collaborative creative expression and active engagement.


About the Role:

We are looking for a Machine Learning Engineer to own the end-to-end lifecycle of ML models in production at Smule, from training and optimization through deployment, monitoring, and iteration. You will work closely with research scientists to bring models off the bench and into scalable, reliable systems that serve millions of users. The ideal candidate is a strong engineer first, with deep practical knowledge of ML systems, a passion for reliability, and an eye for performance.


We strongly encourage candidates with non-traditional backgrounds to apply. If your path into ML engineering came through backend systems, DevOps, audio software, data engineering, or another field, we want to hear from you.


What You'll Be Doing:

  • Design, build, and maintain production ML pipelines encompassing data ingestion, feature engineering, model training, evaluation, and deployment.
  • Optimize models for production constraints including latency, throughput, memory footprint, and cost, using techniques such as quantization, distillation, pruning, and efficient serving architectures.
  • Implement robust monitoring, alerting, and observability for deployed models, covering data drift, prediction quality, and system health.
  • Collaborate with research scientists to integrate new model architectures and training techniques into production systems with minimal friction.
  • Build and improve CI/CD pipelines for ML, including automated testing, validation gates, and staged rollouts.
  • Manage compute infrastructure and costs, making informed tradeoffs between performance, reliability, and budget.


What We're Looking For:

  • Degree (B.S., M.S., or Ph.D.) in Computer Science, Software Engineering, Electrical Engineering, or a related technical discipline, or currently pursuing one.
  • Strong proficiency in Python and experience with deep learning serving (TorchServe, Triton, vLLM, or equivalent).
  • Solid understanding of systems engineering: networking, storage, containerization, orchestration, and monitoring.
  • Ability to reason about tradeoffs between latency, throughput, cost, and model quality.


Bonus Points For:

  • Experience serving large language models or other generative models at scale.
  • Familiarity with audio/music processing pipelines and real-time inference constraints.
  • Experience with Bayesian optimization, bandit algorithms, or adaptive experimentation platforms.
  • Contributions to open-source ML infrastructure projects.


Smule is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, ancestry, age, disability, medical condition, genetic information, marital status, military or veteran status, or any other protected characteristic under federal, state, or local law.


We are committed to creating an inclusive environment for all employees and applicants. If you require a reasonable accommodation during the application or interview process, please let us know.