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Associate Machine Learning Chemistry Jobs (NOW HIRING)

Alsym Energy

Machine Learning Engineer (Malden)

Malden, MA · On-site

$130K - $215K/yr

... Machine Learning Scientist or Engineer to design, build, and deploy agentic AI systems that ... chemistry, and energy systems. The goal is not to build a generic chatbot, but to create reliable ...

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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 Aug 3, 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:
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Associate Machine Learning Chemistry jobs near you
Infographic showing various Associate Machine Learning Chemistry job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 69% Full Time, 28% Part Time, 1% Temporary, and 1% 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 Engineer

Swish Analytics

San Francisco, CA • Remote

$160K/yr

Full-time

Re-posted 16 days ago

Job description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and enterprise clients.

The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to “roll your own” and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.

This position is 100% remote

Responsibilities:

  • Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency.

  • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow.

  • Build, test, deploy and maintain production systems.

  • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages.

  • Support maintenance and optimization of cloud-native EDW and ETL solutions.

  • Maintain and promote best practices for software development, including deployment process, documentation, and coding standards.

  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.

  • Use extensive experience to build, test, debug, and deploy production-grade components.

  • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products.

  • Participate in development of database structures that fit into the overall architecture of Swish systems

Qualifications:

  • Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area

  • 5+ years of demonstrated experience developing and delivering clean and efficient production code to serve business needs

  • A proven background in quantitative analytics, trading, or engineering is required for this position

  • Demonstrated experience developing data science modeling systems and infrastructure at scale

  • Experience with Python and exposure to modern machine learning frameworks

  • Proficient in SQL; experience with MySQL

  • Background and/or interest in Rust preferred

  • Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback

  • Strong communication skills when discussing technical concepts with technical and non-technical colleagues

Base salary: starting at $160,000 base plus bonus potential

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.