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Associate Machine Learning Jobs in Connecticut (NOW HIRING)

Aerotek

Production Associate

Hamden, CT · On-site

$17 - $19/hr

The Production Associate assembles mechanical and electrical components, operates production ... Support cross-training efforts by learning to operate multiple machines and processes across the ...

Aerotek

Production Associate

Centerbrook, CT

$17 - $19/hr

The Production Associate assembles mechanical and electrical components, operates production ... Support cross-training efforts by learning to operate multiple machines and processes across the ...

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Showing results 21-40

All JobsAssociate Machine Learning JobsAssociate Machine Learning Jobs in Connecticut

Associate Machine Learning information

See Connecticut salary details

$23.6K

$124.1K

$304.2K

How much do associate machine learning jobs pay per year?

As of Sep 9, 2026, the average yearly pay for associate machine learning in Connecticut is $124,059.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,000.00 and $172,000.00 per year, depending on experience, location, and employer.

What does an associate machine learning engineer do?

An Associate Machine Learning Engineer assists in designing, developing, and deploying machine learning models under the supervision of senior engineers. They handle tasks such as data preprocessing, model evaluation, and maintaining machine learning pipelines. Associates often collaborate with data scientists, software engineers, and business teams to ensure that machine learning solutions are integrated effectively into products or services. This role is typically entry-level or early career and is a stepping stone toward more advanced machine learning positions.

What are the key skills and qualifications needed to thrive as an associate machine learning engineer?

To thrive as an Associate Machine Learning Engineer, you need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, usually supported by a relevant degree. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience with data processing libraries and version control systems is typically required. Strong analytical thinking, problem-solving ability, and effective collaboration skills help you stand out in this role. These competencies are essential for developing robust models, working efficiently with teams, and delivering impactful data-driven solutions.

What are some common challenges faced by associate machine learning professionals when transitioning from academic projects to real-world business applications?

Associate Machine Learning professionals often find that moving from academic or theoretical projects to business-focused environments introduces new challenges. Real-world datasets can be messy, incomplete, or imbalanced, requiring additional data cleaning and preprocessing. Moreover, business timelines may require rapid prototyping and iterative model development, which is different from the more open-ended nature of academic research. Collaborating with cross-functional teams such as data engineers, product managers, and business stakeholders is also essential to align models with organizational goals. Adapting to these practical aspects is key to succeeding in an Associate Machine Learning role.

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

AspectAssociate Machine LearningData Scientist
Required CredentialsBachelor's degree in CS, Data Science, or related field; some roles may require certifications in ML or AIBachelor's or Master's in CS, Statistics, or related; often requires experience with data analysis and programming
Work EnvironmentEntry-level, team-based projects, focused on supporting ML models and data preprocessingMore autonomous, involved in data analysis, model development, and interpretation
Employer & Industry UsageTech companies, startups, research labs; roles in AI and ML teamsWide range of industries including tech, finance, healthcare, and consulting

While both roles involve working with data and machine learning, an Associate Machine Learning typically focuses on supporting ML projects with less experience, whereas a Data Scientist has broader responsibilities including data analysis, model development, and strategic insights. The roles often overlap but differ in scope and experience level.

What are the most commonly searched types of Machine Learning jobs in Connecticut?

The most popular types of Machine Learning jobs in Connecticut are:

What cities in Connecticut are hiring for Associate Machine Learning jobs?

Cities in Connecticut with the most Associate Machine Learning job openings:

Associate Machine Learning jobs near you

Associate w Tenure, Full Professor

New Haven, CT • On-site

Yale University
Colleges, Universities, and Professional Schools • 10K+ employees
Learn more about Yale Universityexternal

Full-time

Re-posted 29 days ago

Yale University rating

8.2

Company rating: 8.2 out of 10

Based on 65 frontline employees who took The Breakroom Quiz

152nd of 631 rated colleges and universities

Job description

Description
Associate w Tenure or Full Professor of Biomedical Informatics & Data Science
The Department of Biomedical Informatics and Data Science (BIDS)at Yale University School of Medicine invites applications for Associate w/ Tenure and Full Professor positions in the tenure track. Applicants must have an M.D. and/or Ph.D. or equivalent degree and have demonstrated excellent qualifications in research and education. Multiple positions will be filled each year. Areas of interest include:
• Artificial intelligence in medicine
• Biomedical data modeling and ontologies
• Biomedical data science
• Biomedical natural language processing and knowledge representation
• Clinical informatics
• Clinical research informatics
• Computational biology and bioinformatics
• Genomics, transcriptomics, proteomics
• Global health informatics
• Health disparities and outcomes research
• Human computer interaction and usability
• Image analysis
• Machine learning and statistical learning
• Modeling & simulating molecular structures and cellular networks
• Population health informatics
• Precision medicine
• Privacy technology
Responsibilities include establishing a vigorous and independently funded research program while supervising and mentoring students with diverse backgrounds plus contributing to the graduate and medical school educational missions. We seek individuals with strong records of independent creative accomplishments, who will interact productively with colleagues within the Department and across Yale School of Medicine and the University. Justice, diversity, equality, and inclusion for faculty, staff, and trainees are core values for BIDS. Applications from individuals belonging to under-represented groups in informatics and data science are encouraged. We foster an environment of collaboration and scientific discovery, and we value the exchange of new ideas and novel approaches to research, training, and service. Joint appointments with other departments will also be supported. Leadership roles will be considered according to the candidates' interests and prior accomplishments. Strong scientific, management, and interpersonal skills are required. Appointment at the Assistant, Associate or Full Professor levels will be based on the candidate's qualifications and experience.
Biomedical Informatics and Data Science (BIDS) at Yale University is a newly established self-standing Department within Yale School of Medicine, which has a rich history of pre-eminence in biomedical research and clinical care. BIDS faculty are known nationally and internationally for their contributions to biomedical informatics and data science and multidisciplinary collaborations. Today, research at the Yale School of Medicine encompasses a broad range of fields, withresearchers aiming to understand, prevent, and treat human disease in a personalized and equitable manner. Yale's new findings in basic and translational science inform and synergize with impactful clinical research, and with implementation and evaluation of systems in real clinical settings. For more details, see https://medicine.yale.edu/biomedical-informatics-data-science/.
Consideration of applications will begin 10/1/2024.
Yale University is an Equal Opportunity/Affirmative Action Employer. We seek candidates who embrace and reflect diversity in the broadest sense. Yale values diversity among its students, staff, and faculty and strongly welcomesapplications from women, persons with disabilities, protected veterans, and underrepresented minorities.
Application Instructions
Please submit a cover letter describing qualifications, along with a CV, a two-page summary of current and proposed research, and three letters of reference to one of the following Interfolio websites:
For interested Associate w Tenure, Full Professors: http://apply.interfolio.com/155167

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