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Associate Machine Learning Jobs in Massachusetts

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... our associates work and provide value to our customers. * Design, develop, test, deploy, and ...

Lead Machine Learning Engineer

Cambridge, MA

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... our associates work and provide value to our customers. * Design, develop, test, deploy, and ...

About the Opportunity JOB SUMMARY The Associate AI Engineer will be responsible for designing ... Machine Learning Engineering: Demonstrated experience in the full ML lifecycle including data ...

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Showing results 1-20

Associate Machine Learning information

See Massachusetts salary details

$26.5K

$139.3K

$341.5K

How much do associate machine learning jobs pay per year?

As of Sep 1, 2026, the average yearly pay for associate machine learning in Massachusetts is $139,272.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,900.00 and $193,100.00 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 Massachusetts?

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

Senior Machine Learning Engineer - Hybrid

Manulife and John Hancock

Boston, MA • On-site

$175K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago


Job description

Employer: John Hancock Life Insurance Company (USA)
Job Site: 200 Berkeley Street, Boston, MA 02116
Job Title: Senior Machine Learning Engineer
Job Duties:
Package models, automate workflows, and operationalize analytics solutions to generate business value for organization's insurance division as member of U.S. based Advanced Analytics Team. Duties include:
  • Design, recommend, and implement platforms and infrastructure using MLOps/LLMOps best practices;
  • Collaborate with data scientists and data engineers to design and implement scalable and efficient machine learning pipelines;
  • Evaluate and optimize machine learning models for performance and scalability;
  • Deploy machine learning models into production and monitor performance;
  • Manage data science infrastructure to streamline model development and deployment;
  • Support development and deployment of high-quality Generative AI technologies including prompt engineering and RAG applications, and fine-tuning LLM models using Azure AI Studio;
  • Propose appropriate tools including languages, libraries, and frameworks for implementing projects;
  • Work closely with infrastructure architects to design scalable and efficient solutions;
  • Collaborate with cross-functional teams to integrate machine learning models into existing systems and processes;
  • Keep abreast of latest advancements in machine learning, MLOps, and LLMOps techniques, and contribute to continuously improving organization's machine learning capabilities; and
  • Mentor associates and peers on MLOps best practices.

Work Arrangement requirement: Hybrid from Boston office (3 days from office, 2 days from home)
Minimum Requirements:
Master's degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.
Experience must include the following, which may be gained concurrently:
Minimum Requirements:
Master's degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.
Experience must include the following, which may be gained concurrently:
Minimum Requirements:
Master's degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.
Experience must include the following, which may be gained concurrently:
  • 3 years of experience developing and deploying machine learning models for model training, optimization, evaluation, and production deployment through APIs, microservices, or cloud-based serving infrastructure using Python, TensorFlow, PyTorch, Scikit-learn, Keras, or XGBoost.
  • 3 years of experience deploying and managing infrastructure using Linux OS, containerization technologies (Docker, Kubernetes), relational databases (PostgreSQL, MySQL, and Oracle) and NoSQL databases (MongoDB, Cassandra, Elasticsearch and Redis) using AWS, Azure or GCP cloud platforms.
  • 3 years of experience designing and building scalable ETL pipelines and feature engineering workflows for large-scale datasets using distributed processing frameworks including Apache Spark (PySpark, Spark SQL), Hadoop ecosystem tools, or cloud-based big data services including Databricks and EMR.
  • 2 years of experience developing and deploying Large Language Models including BERT, GPT-series, T5, or LLaMA, or other transformer-based NLP models using cloud-based platforms and open-source frameworks.
  • 3 years of experience designing hybrid machine learning systems combining rule-based decision engines with ML models for fraud detection, compliance, claims adjudication, or automated decision-making in regulated environments.
  • 3 years of experience applying machine learning algorithms, statistical modeling, and data analysis techniques for model optimization, generating actionable insights, and working with structured and unstructured data to solve business problems in financial services, fintech, insurance, or other regulated industries.
  • 3 years of experience with Agile development methodologies including Scrum, Kanban, or SAFe for sprint planning, iterative development cycles, and cross-functional team collaboration in enterprise environments.
  • 2 years of experience developing and deploying computer vision models for document processing, OCR, information extraction, or image classification using OpenCV, Tesseract, or cloud-based vision APIs.

Salary: $175,000 per year
The role being advertised is an existing vacancy.
About Manulife and John Hancock
Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html.
Manulife is an Equal Opportunity Employer
At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.
It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact hr@manulife.com.
Referenced Salary Location
Boston, Massachusetts
Working Arrangement
Hybrid
Salary range is expected to be between
$107,450.00 USD - $199,550.00 USD
Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. The actual salary will vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training. If you are applying for this role outside of the primary location, please contact hr@manulife.com for the salary range for your location.
Manulife/John Hancock offers eligible employees a wide array of customizable benefits, including health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension/401(k) savings plans and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in the U.S. includes up to 11 paid holidays, 3 personal days, 150 hours of vacation, and 40 hours of sick time (or more where required by law) each year, and we offer the full range of statutory leaves of absence.
We use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in the application process. For more information, please refer to our personal information collection statement.
Know Your Rights I Family & Medical Leave I Employee Polygraph Protection I Right to Work I E-Verify
Company: John Hancock Life Insurance Company (U.S.A.)