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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 Jun 19, 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 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.

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.

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 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.
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 June 2026, with employment types broken down into 2% As Needed, 32% Full Time, 64% Part Time, and 2% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $133,062 per year, or $64 per hour.
Machine Learning Platform Engineer

Machine Learning Platform Engineer

Schrödinger

New York, NY • On-site

$120K - $145K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago

Job description

Schrödinger seeks a Machine Learning (ML) Platform Engineer to join us in our mission to improve human health and quality of life through the development, distribution, and application of advanced computational methods!
As a member of the Machine Learning team, you'll build scalable software systems that enable scientists and engineers to train, deploy, and analyze machine learning models at scale. Our machine learning platform, LiveDesignML, supports applications ranging from molecular property prediction and generative chemistry to protein modeling.
Who will love this job:
  • A highly-skilled software engineer who understands coding fundamentals, is experienced with Python, and has run projects end-to-end, from prototype to production
  • An ML expert who's familiar with PyTorch, TensorFlow, and scikit-learn
  • An analytical thinker who enjoys working with multi-dimensional data, solving data-processing problems, and digging through complex systems to solve technical problems
  • A polymath who's excited about working collaboratively in an interdisciplinary environment and comfortable with self-directed research and problem exploration

What you'll do:
  • Design and develop infrastructure supporting machine learning training, inference, and experimentation workflows
  • Build and maintain production systems that enable scientists to run large-scale ML workloads
  • Collaborate with scientists, ML researchers, and engineers to translate research ideas into reliable software tools
  • Contribute to backend services and APIs supporting ML workflows and platform features
  • Improve developer workflows, testing infrastructure, and deployment automation
  • Participate in code reviews and contribute to engineering best practices across the team
  • Pitch in on frontend components of the ML platform web interface when needed

What you should have:
  • BS, MS, or PhD in Computer Science, Machine Learning, Software Engineering, Mathematics, Physics, Chemistry, or a related field

Experience with the following is nice to have, but not required:
  • Cloud platforms like AWS or GCP
  • Containerization and orchestration (e.g., Docker, Kubernetes, Argo Workflows, Helm charts, etc.)
  • CI/CD systems and modern software development workflows (e.g., Jenkins, GitHub Actions, etc.)
  • Monitoring, logging, or observability systems
  • Distributed computing or large-scale ML workloads
  • ML training pipelines or experiment management
  • Data processing pipelines or large-scale data analysis
  • Source control systems (Git or similar)
  • Web application development (e.g., React, TypeScript, REST APIs)
  • Interest in scientific computing, chemistry, biology, physics, or related domains

Pay and perks:
Schrödinger understands it's people that make a company great. Because of this, we're prepared to offer a competitive salary, equity-based compensation, and a wide range of benefits that include healthcare (with dental and vision), a 401k, pre-tax commuter benefits, a flexible work schedule, and a parental leave program. We have regular catered meals in the office, a company culture that is relaxed but engaged, and over a month of paid vacation time. Our Office Management team also plans a myriad of fun company-wide events. New York is home to our largest office, but we have teams all over the world. Schrödinger is honored to have been included in Crain's New York Best Places to Work, BuiltIn's NYC Best Place to Work, and Newsweek's list of America's 100 Most Loved Workplaces.
Estimated base salary range: $120,000 - $145,000. Actual compensation package is dependent on a number of factors, including, for example, experience, education, degrees held, market data, and business needs. If you have any questions regarding the compensation for this role, do not hesitate to reach out to a member of our Strategic Growth team.
Sound exciting? Apply today and join us!
As an equal opportunity employer, Schrödinger hires outstanding individuals into every position in the company. People who work with us have a high degree of engagement, a commitment to working effectively in teams, and a passion for the company's mission. We place the highest value on creating a safe environment where our employees can grow and contribute, and refuse to discriminate on the basis of race, color, religious belief, sex, age, disability, national origin, alienage or citizenship status, marital status, partnership status, caregiver status, sexual and reproductive health decisions, gender identity or expression, sexual orientation, or any other protected characteristic. To us, "diversity" isn't just a buzzword, but an important element of our core principles and key business practices. We believe that diverse companies innovate better and think more creatively than homogenous ones because they take into account a wide range of viewpoints. For us, greater diversity doesn't mean better headlines or public images - it means increased adaptability and profitability.

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