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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 · 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 ...

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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 Jul 9, 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:
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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, 67% Full Time, 30% 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.

Associate, Machine Learning Engineer

Cantor Fitzgerald Securities

Manhattan, NY

Full-time

Posted 22 days ago

Job description

We are seeking an early-career engineer to join our team and play a vital role in developing and enhancing AI-powered applications for our financial services business. The ideal candidate will have a solid foundation in software development, hands-on experience with modern AI tools, and a keen interest in understanding the behavior of language models in real-world applications. As an Associate, you will have the opportunity to work closely with our experienced engineers and contribute to the growth and success of our innovative AI initiatives.
Company overview: 

Built upon the foundation of innovative technology and exceptional talent, BGC is a pioneering global brokerage and financial technology company servicing the financial markets. We are agile and dynamic in our approach, delivering world-class products to our diverse customer base daily. Our Financial Services business provides a full range of trade execution and broker-dealer services. 

The benefit of BGC's integrated platform is that it gives customers flexibility and choice in price discovery, execution, and processing of their transactions, through voice, hybrid, or fully electronic brokerage options. In addition, our BGC Trader and BGC Market Data platforms offer financial technology solutions, market data and analytics related to financial instruments and markets.

Agency Notice:

BGC Group & affiliates do not accept agency resumes. Please do not forward resumes to our job alias, employees or any other company location. BGC Group & affiliates are not responsible for any fees related to unsolicited resumes. Please contact the Recruitment function for additional details. 
  • Bachelor's degree in a technical field (computer science, machine learning, mathematics, etc.) or equivalent practical experience.
  • Experience contributing to production-level software development, internships, research, or substantial personal projects.
  • Strong programming skills in Python, with a focus on writing clear, tested, and maintainable code.
  • Hands-on experience with web services, data integration, testing, logging, and monitoring.
  • Practical knowledge of building with LLMs and understanding common failure modes.
  • Ability to test, evaluate, and improve LLM-powered applications.
  • Grounding in machine learning, statistics, and experimental design, with a knack for technical documentation.
  • Excellent communication skills and a collaborative mindset.
  • Interest in applying AI responsibly in financial services.
  • Familiarity with agentic workflows, evaluation tools, and cloud deployment is a plus.

Compensation

  • Collaborate with a cross-functional team to build, evaluate, and improve AI-powered financial services applications.
  • Design and implement machine learning models and algorithms to solve complex business problems.
  • Work with large language models (LLMs) and understand their behavior and potential failure modes.
  • Conduct testing and evaluation of LLM-powered applications, analyzing failures and defining success metrics.
  • Apply machine learning, statistics, and experimental design principles to reason about model behavior.
  • Communicate effectively with product, engineering, and business partners to align on project goals.
  • Ensure responsible AI practices are followed, considering privacy, security, and appropriate automation.
  • Stay updated with the latest advancements in AI and machine learning technologies.
  • Document and present project progress and findings to stakeholders.
  • Provide support and mentorship to junior team members as needed.

Apply