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Fraud Detection Machine Learning Jobs in Massachusetts

Eka

Machine Learning / Computer Vision Engineer

Boston, MA · On-site

$90 - $130/hr

Our team consists of pioneers in robotics and machine learning. We are now hiring to scale our R&D ... Practical experience with visual representation learning, object detection, segmentation, pose ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you ...

VideaHealth

Senior Machine Learning Engineer

Boston, MA · On-site

$170K - $205K/yr

Implement monitoring, drift detection, evaluation protocols, and retraining or update workflows for ... Requirements * 4+ years building and deploying machine learning systems in production, ideally with ...

ASUS

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

The ASUS Robotics & AI Center is seeking a Senior Machine Learning Engineer to join our global ... Evaluate and implement state-of-the-art techniques in deep learning, object detection, and visual ...

Xometry

Staff Machine Learning Engineer

Waltham, MA · On-site

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a ... Demonstrated experience with MLOps practices: model monitoring, data and concept drift detection ...

Xometry

Staff Machine Learning Engineer

Waltham, MA · On-site

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a ... Demonstrated experience with MLOps practices: model monitoring, data and concept drift detection ...

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Fraud Detection Machine Learning information

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How much do fraud detection machine learning jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for fraud detection machine learning in Massachusetts is $19.71, according to ZipRecruiter salary data. Most workers in this role earn between $16.30 and $21.01 per hour, depending on experience, location, and employer.

What is fraud detection using machine learning?

Fraud detection using machine learning involves leveraging algorithms and data analysis techniques to identify suspicious or fraudulent activities in various domains, such as banking, e-commerce, or insurance. These systems analyze large volumes of transaction data to detect patterns or anomalies that may indicate fraud. Machine learning models can adapt over time, improving their accuracy as they are exposed to more data. This approach helps organizations automate and enhance their ability to prevent, detect, and respond to fraudulent behavior efficiently.

What are some common challenges faced by professionals working in fraud detection machine learning, and how can they be addressed?

Professionals in Fraud Detection Machine Learning often face challenges such as dealing with highly imbalanced datasets, rapidly evolving fraud patterns, and the need for real-time detection. Managing data imbalance requires careful selection of evaluation metrics and specialized algorithms. Staying ahead of new fraud tactics involves continuous model retraining and close collaboration with domain experts. Additionally, integrating machine learning solutions with existing systems often requires cross-functional teamwork with IT, security, and compliance teams.

What are the key skills and qualifications needed to thrive as a fraud detection machine learning specialist, and why are they important?

To thrive as a Fraud Detection Machine Learning Specialist, you need strong expertise in machine learning, statistical analysis, and programming languages like Python or R, typically supported by a degree in computer science, data science, or a related field. Familiarity with tools such as TensorFlow, Scikit-learn, SQL databases, and experience with big data platforms or cloud services is highly valuable. Critical thinking, attention to detail, and effective communication are crucial soft skills for identifying complex fraud patterns and collaborating with interdisciplinary teams. These competencies are vital for developing accurate models that protect organizations from financial losses and maintain trust with customers.

What is the difference between Fraud Detection Machine Learning vs Fraud Analyst?

AspectFraud Detection Machine LearningFraud Analyst
CredentialsData science, machine learning certifications, programming skillsFinance, criminal justice degrees, analytical skills
Work EnvironmentData-driven, tech-focused, often in financial or e-commerce sectorsInvestigative, report-focused, in financial institutions or insurance companies
Employer & IndustryTech companies, banks, e-commerce platformsFinancial institutions, insurance firms, retail

Fraud Detection Machine Learning involves developing algorithms to identify fraudulent activities automatically, relying heavily on data analysis and programming. Fraud Analysts manually investigate suspicious cases and interpret data insights. While both roles aim to prevent fraud, Machine Learning specialists focus on building models, whereas Fraud Analysts focus on case investigation and decision-making.

What are popular job titles related to Fraud Detection Machine Learning jobs in Massachusetts?

For Fraud Detection Machine Learning jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Fraud Detection Machine Learning jobs in Massachusetts look for?

The top searched job categories for Fraud Detection Machine Learning jobs in Massachusetts are:

What cities in Massachusetts are hiring for Fraud Detection Machine Learning jobs?

Cities in Massachusetts with the most Fraud Detection Machine Learning job openings:

Fraud Detection Machine Learning jobs near you
Infographic showing various Fraud Detection Machine Learning job openings in Massachusetts as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $41,007 per year, or $19.7 per hour.

Senior Machine Learning Operations Engineer

AgZen

Somerville, MA • On-site

$114K - $156K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 20 days ago

Key responsibilities

  • Own the architecture, execution, and operational excellence of large‑scale, cloud‑native pipelines for sensor data ingestion, processing, labeling, and validation.

  • Build diagnostic tooling to root cause pipeline and recommendation issues, ensure proper logging, and develop dashboards for monitoring.

  • Collaborate with cross-functional teams to design, build, and maintain robust data pipelines and support model deployment and performance tracking.

Job description

About AgZen:
AgZen is a fast-growing precision agriculture company headquartered in Somerville, MA, built on MIT research and focused on one problem: making crop spraying more efficient. Our flagship product, RealCoverage, is the world's first system that measures and controls droplet coverage at the leaf level, giving growers real-time visibility into spray performance and cutting chemical and water use by up to 50% without sacrificing yield.
We are a small, technically deep team working at the intersection of fluid mechanics, computer vision, AI, and real agricultural environments. If you want to build technology with measurable impact on how the world grows food, this is the place to do it.
About the Role
We are looking for a sharp, tenacious, and thorough Senior Machine Learning Operations (MLOps) Engineer to join our team. As part of the the perception team, you'll own the operational layer around of machine learning models. This role will be responsible for the intake and leveraging crop protection data collected from RealCoverage units installed on sprayers all around the world which is then used improve our CV pipeline and Recommendation Engine. This role will be an essential component of AgZen's measurement focus group. Strong communication, flexibility, teamwork, the desire to take on different responsibilities and own them will all be essential skills for a successful applicant.
This role is located in Somerville, MA (Boston area) with work required to be in-person.
What You'll Do
  • Own the architecture, execution, and operational excellence of large‑scale, cloud‑native pipelines for multimodal sensor data ingestion, processing, labeling, and validation.
  • Champion model traceability by building a clear lineage for every production model. Track what data trained it, what code produced it, what validation it passed, and how it's performing. Evaluate and recommend tooling for versioning, metadata, and model registry
  • Partner with data scientists to detect data quality issues, detect drift in upstream sources, and ensure features stay fresh and reliable
  • Track model drift over weeks, flag slow degradation before it crosses a threshold, surface feature freshness problems before they cascade
  • Build diagnostic tooling to root cause pipeline and recommendation issues quickly. Ensure the right context is logged at each stage, candidates, features, serving context, and building the dashboards to tie it collectively
  • Own automated gates that block bad deployments and assist in running model issue retrospectives
  • Work with ML engineers, data engineers, and stakeholders to coordinate on post-deployment metrics, defining what metrics to collect after deployment and why they matter
  • Build tooling and support non-technical domain experts in understanding perception system performance and identifying opportunities for pipeline improvement
  • Collaborate closely with cross-functional teams of software engineers, machine learning scientists, product specialists, and researchers to design, build, and maintain robust data pipelines grounded in sound data organization, domain knowledge, and careful analysis
  • Communicate technical findings, data characteristics, and limitations clearly and effectively to both internal partners and external collaborators

What We're Looking For
Required:
  • Bachelor's or graduate degree in Computer Science, Electrical Engineering, or a closely related field
  • 5+ years of experience building large-scale distributed systems, applications, or advanced ML systems‑scale distributed systems, applications, or advanced ML systems
  • Experience with MLOps, data pipelines, and cloud distributed systems
  • Proficiency in Python for system‑level and performance‑critical implementation
  • Experience operating end‑to‑end data or ML pipelines for reliability, scale, and observability
  • Communication skills that align collaborators and drive execution across functions
  • Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow)
  • A record of ownership, accountability, and customer‑focused engineering
  • Proven track record of designing robust frameworks with high-quality, durable APIs
  • Deep understanding of machine learning algorithms with hands‑on application
  • Expertise in building reliable, high-performance, and cost-efficient systems on modern cloud infrastructure‑performance
  • Robust SQL skills and comfort digging into data distributions, feature health, and model behavior

Preferred:
  • Experience with the field of agriculture or related fields such as environmental or life sciences
  • Experience with data science based on real-world physical sensors data
  • Experience with vision-based ML
  • Experience creating intuitive data visualization tools that make complex data approachable for non-technical users
  • Prior experience in developing machine-learning models relevant to biological or crop protection outcomes
  • Advanced scientific Python (NumPy, Pandas, scikit-learn) and hands-on experience with PyTorch and/or TensorFlow, including training and deploying neural networks
  • Experience operating recommendation systems at scale

What We Offer
  • The opportunity to make an immediate and visible impact in a fast-growing company
  • Early-employee equity
  • 401(k) with employer matching at 6 months of employment
  • 6 weeks of PTO per calendar year
  • 12 paid holidays
  • Medical, Dental and Vision insurance

The salary range for this position is $150,000 - $200,000 depending on skills and qualifications evaluated on a per candidate basis.

Apply