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Associate 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 ...

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Associate Machine Learning Chemistry information

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$31.5K

$133.1K

$314.5K

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

As of May 30, 2026, the average yearly pay for associate machine learning chemistry in the United States is $133,062.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,000.00 and $202,000.00 per year, depending on experience, location, and employer.

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

To thrive as an Associate Machine Learning Chemistry professional, you need a solid background in chemistry, data analysis, and machine learning, typically supported by a relevant degree such as chemistry, computer science, or a related field. Experience with programming languages like Python, machine learning libraries (e.g., TensorFlow, scikit-learn), and cheminformatics software is highly valued. Strong problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly are crucial soft skills. These competencies enable effective collaboration on interdisciplinary teams and the development of innovative solutions in computational chemistry research.

How does an Associate Machine Learning Chemistry professional typically collaborate with research scientists and engineers?

As an Associate Machine Learning Chemistry professional, you will frequently work alongside research scientists and chemical engineers to develop predictive models and analyze experimental data. Collaboration involves translating chemical problems into machine learning tasks, sharing insights from model results, and participating in interdisciplinary meetings to refine research objectives. Effective communication and teamwork are essential, as you may be required to explain machine learning concepts to non-technical colleagues and integrate their domain expertise into your models. This collaborative environment fosters both scientific discovery and professional growth.

What are Associate Machine Learning Chemists?

Associate Machine Learning Chemists are professionals who combine expertise in chemistry with skills in machine learning to analyze chemical data, develop predictive models, and accelerate scientific discovery. They often work on tasks like predicting molecular properties, optimizing chemical reactions, and supporting drug discovery efforts using computational tools. Typically, these roles require a strong foundation in chemistry, programming experience (often in Python), and familiarity with machine learning libraries. Associate positions are generally entry-level or early-career roles, providing support to senior scientists and data scientists in research and development teams.

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

AspectAssociate Machine Learning ChemistryAssociate Data Scientist
Required CredentialsBachelor's or Master's in Chemistry, Data Science, or related fields; familiarity with ML frameworksBachelor's or Master's in Data Science, Statistics, Computer Science; programming skills in Python/R
Work EnvironmentResearch labs, pharmaceutical or chemical companies, biotech firmsTech companies, finance, healthcare, consulting firms
Employer & Industry UsageUsed in industries applying ML to chemical data, drug discovery, materials scienceApplied across industries analyzing large datasets, predictive modeling

Associate Machine Learning Chemistry focuses on applying machine learning techniques specifically to chemical and scientific data, often within research or pharmaceutical settings. In contrast, Associate Data Scientist has a broader scope, working with various data types across multiple industries. Both roles require strong analytical skills and familiarity with ML tools, but their industry focus and data types differ.

More about Associate Machine Learning Chemistry jobs
What cities are hiring for Associate Machine Learning Chemistry jobs? Cities with the most Associate 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 Associate Machine Learning Chemistry jobs? States with the most job openings for Associate Machine Learning Chemistry jobs include:
What job categories do people searching Associate Machine Learning Chemistry jobs look for? The top searched job categories for Associate Machine Learning Chemistry jobs are:
Associate Machine Learning Chemistry jobs near you
Infographic showing various Associate Machine Learning Chemistry job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 63% Full Time, 35% Part Time, and 1% Contract. Highlights an 75% Physical, and 25% Remote job distribution, with an average salary of $133,062 per year, or $64 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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