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Associate Machine Learning Jobs in Massachusetts

Capital One

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 ...

Capital One

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 ...

Redhat

Machine Learning Engineer

Boston, MA · On-site +1

$136K - $225K/yr

Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are ...

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Showing results 1-20

All JobsAssociate Machine Learning JobsAssociate Machine Learning Jobs in Massachusetts

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 Jul 21, 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 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 key skills and qualifications needed to thrive as an Associate Machine Learning Engineer, and why are they important?

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 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 most commonly searched types of Machine Learning jobs in Massachusetts? The most popular types of Machine Learning jobs in Massachusetts are:
What are popular job titles related to Associate Machine Learning jobs in Massachusetts? For Associate Machine Learning jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Associate Machine Learning jobs in Massachusetts look for? The top searched job categories for Associate Machine Learning jobs in Massachusetts are:
Associate Machine Learning jobs near you
Associate Director, Machine Learning (Core Algorithms)

Associate Director, Machine Learning (Core Algorithms)

WHOOP

Boston, MA • On-site

Full-time

Posted 21 days ago

Job description

Job Summary:
WHOOP is dedicated to enhancing human performance and healthspan through advanced insights into physiological data. They are looking for an Associate Director of Machine Learning to lead the development of cloud-based algorithms that provide insights on sleep, recovery, and training for their members. This role involves overseeing a team of ML scientists and engineers, ensuring algorithm quality, and collaborating with various teams to innovate and improve WHOOP's offerings.
Responsibilities:
• Lead the cloud ML team responsible for the algorithms powering sleep, recovery, and training
• Directly manage applied ML scientists and ML engineers; provide coaching, career development, and performance feedback that grows individual contributors into strong technical leaders
• Ensure the technical quality bar for algorithm development is maintained by establishing the processes, reviews, and standards that guarantee rigor from research through deployment, and diving into designs and architectural decisions where necessary
• Help drive the vision for what WHOOP algorithms and next-generation sensors can enable; advocate for member experience and push the boundaries of what our data makes possible
• Ensure cloud algorithms remain compatible with future hardware generations; partner with Sensor Intelligence and Hardware to evolve proof-of-concept algorithms that leverage new sensor capabilities and bring them to production readiness
• Establish and improve development lifecycle practices: experiment management, model validation, deployment pipelines, and production monitoring
• Partner with ML Platform / MLOps to define requirements and drive maturity improvements across experiment tracking, model monitoring, deployment automation, and observability
• Drive cross-functional alignment with Sensor Intelligence, Product, Software Engineering, and Research teams
Qualifications:
Required:
• 8+ years of experience in machine learning or applied data science, with hands-on experience developing and shipping ML models for a consumer product
• 4+ years of people leadership experience directly managing machine learning scientists/engineers, with demonstrated growth of team members and a track record of building high-performing teams
• Experience scaling a production ML organization: growing teams and leaders, identifying gaps in the development lifecycle, and driving improvements that increase velocity, reliability, and rigor
• Deep product sense: ability to think about algorithms from the member's perspective, drive the vision for what algorithms can enable, and ensure the team is building toward meaningful user outcomes
• Ability to evaluate technical designs, guide architectural decisions, and ensure quality at the system level, without needing to write code day-to-day
• Experience defining and driving cross-functional programs with engineering, product, and science partners
• Strong communication skills with the ability to translate complex ML concepts to diverse audiences including product, engineering, and executive stakeholders
Preferred:
• Experience building algorithms using physiological or wearable sensor data (e.g., PPG, accelerometer, temperature, bioimpedance)
• Experience managing through hardware-coupled development timelines where sensor availability and device generations constrain algorithm roadmaps
• Familiarity with time-series modeling, sequential data, and the specific challenges of continuous physiological monitoring
Company:
WHOOP provides wearable fitness technology and a subscription platform that tracks physiological data for health and performance insights. Founded in 2012, the company is headquartered in Boston, USA, with a team of 501-1000 employees. The company is currently Late Stage.
Whoop logo

About Whoop

Sourced by ZipRecruiter

At WHOOP, we're on a mission to unlock human performance. WHOOP empowers users (Olympians, Professional Athletes, Fitness Enthusiasts, etc) to perform at a higher level through a deeper understanding of their bodies and daily lives.

Industry

Fitness and sports centers

Company size

501 - 1,000 Employees

Headquarters location

Boston, MA, US

Year founded

2012

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