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Fraud Detection Machine Learning Jobs in Boston, MA

Our products help detect harm, prevent fraud, and build safer, more trusted online and real-world ... We're looking for a Machine Learning Operations Engineer to own and scale the production inference ...

Fraud Investigator

Newton, MA ยท On-site

$75/hr

Assess fraud prevention and detection controls, processes and technology and define and create ... machine learning capabilities. * Build and sustain relationships with subject matter experts in ...

Our products help detect harm, prevent fraud, and build safer, more trusted online and real-world ... We're looking for a Machine Learning Operations Engineer to own and scale the production inference ...

Our products help detect harm, prevent fraud, and build safer, more trusted online and real-world ... We're looking for a Machine Learning Operations Engineer to own and scale the production inference ...

Build and maintain data pipelines for bot detection and content moderation using Python, Snowflake ... with machine learning pipelines and model deployment * Background in cybersecurity or anti-fraud ...

Senior Machine Learning Engineer

Boston, MA ยท On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development ... This includes handling missing values, outlier detection, feature engineering, and data ...

Senior Machine Learning Engineer

Boston, MA ยท Remote

$125K - $165K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development ... This includes handling missing values, outlier detection, feature engineering, and data ...

Senior Machine Learning Engineer

Boston, MA ยท On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development ... This includes handling missing values, outlier detection, feature engineering, and data ...

Senior Machine Learning Engineer

Boston, MA

$113K - $155K/yr

Implement real-time monitoring systems to detect data drift, model decay, and performance ... Champion machine learning best practices, including responsible and ethical AI development ...

Senior Machine Learning Engineer

Boston, MA ยท On-site +1

$161K - $246K/yr

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

Lead Machine Learning Engineer

Cambridge, MA ยท 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 ...

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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 Jun 14, 2026, the average hourly pay for fraud detection machine learning in Boston, MA is $19.61, according to ZipRecruiter salary data. Most workers in this role earn between $16.20 and $20.91 per hour, depending on experience, location, and employer.

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 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 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 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 are popular job titles related to Fraud Detection Machine Learning jobs in Boston, MA? For Fraud Detection Machine Learning jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Fraud Detection Machine Learning jobs in Boston, MA look for? The top searched job categories for Fraud Detection Machine Learning jobs in Boston, MA are:
What cities near Boston, MA are hiring for Fraud Detection Machine Learning jobs? Cities near Boston, MA with the most Fraud Detection Machine Learning job openings:
Machine Learning Operations Engineer

Machine Learning Operations Engineer

Modulate

Somerville, MA โ€ข On-site, Remote

$150 - $200K/hr

Full-time

Medical, Dental, Vision, PTO

Posted 29 days ago


Job description

Modulate is the leader in conversational voice intelligence. We enable enterprises to deeply understand how people communicate and take timely action based on those insights. Our products help detect harm, prevent fraud, and build safer, more trusted online and real-world voice environments. We are building a Conversation Intelligence Platform - APIs, workflows, and applications that bring voice understanding to customers at enterprise scale.

We're looking for a Machine Learning Operations Engineer to own and scale the production inference systems behind Modulate's machine learning models. This role will focus on ensuring high availability, reliability, and efficiency of deployed models across our APIs and enterprise products as we rapidly grow in customer usage and model demand.

Your Impact

  • Own the reliability and performance of ML model inference systems in production

  • Ensure high availability of deployed models across APIs and enterprise products

  • Build systems to handle scaling, load variability, and production traffic growth

  • Reduce operational burden through better tooling, automation, and processes

  • Help define how Modulate runs ML systems at scale with reliability and efficiency

What You Will Do

  • Deploy, monitor, and maintain production machine learning inference systems

  • Oversee fleets of inference machines and ensure system health and performance

  • Design monitoring, alerting, and incident response systems for ML workloads

  • Participate in on-call rotations and lead incident response and debugging

  • Build systems and processes for scaling inference infrastructure under variable load

  • Improve reliability and observability of production ML services

  • Collaborate on infrastructure-as-code for production deployments

  • Support or contribute to GPU-based training and inference infrastructure

  • Work closely with ML and engineering teams to ensure smooth model deployments

  • (Optional growth area) Optimize model inference performance and latency

What We Are Looking For

  • Experience deploying and maintaining production software systems

  • Experience building monitoring and alerting systems for production environments

  • Experience with on-call rotations and incident response

  • Strong experience with AWS, Python, and Linux

  • Exposure to PyTorch or similar ML frameworks

  • Experience working with GPU-based applications and basic GPU tooling (drivers, runtime, monitoring)

  • Strong debugging and systems thinking skills

  • Ability to operate calmly in production incident environments

Nice to Have

  • Experience with ML model serving systems or dedicated model servers

  • Experience monitoring GPU performance for inference workloads

  • Experience optimizing machine learning model inference

  • Familiarity with audio or multimedia data (codecs, streaming, real-time systems)

  • Experience with infrastructure-as-code (e.g., Terraform, CloudFormation)

Benefits

  • Competitive salary + equity

  • Full health, dental, and vision coverage

  • Flexible PTO with strong culture of taking it

  • Weekly team lunches with dietary accommodations

  • Hybrid work with core in-office days and flexible remote options

  • Leadership and technical learning sessions

  • Career development and continued learning support

  • Up to 8 weeks work-from-anywhere policy

  • A deeply inclusive, human-centered culture

Pay Transparency
Modulate believes in transparency as a cornerstone of equity and trust. Compensation for this role is based on seniority, skills, and experience.

  • Salary: $150-$200K

  • Equity: Offered

  • Other perks: HSA, FSA, 15 holidays, professional growth resources

About Modulate
Modulate is on a mission to make voice a force for good online. Our tools help communities thrive by proactively detecting toxic behavior, protecting user identity, and empowering safety teams. We're trusted by leaders in gaming and beyond-and we're growing fast. We believe that great cultures don't just happen. That's why we've built a foundation of intentional systems: from bias-reducing hiring practices to transparent pay to tools that help teams collaborate across communication styles. At Modulate, we treat people like people-and we're building technology that does the same.

Ready to join us? Apply here or reach out directly-we're excited to meet you.

A quick note as you apply

  • Please apply through the website rather than emailing [emailย protected]

  • For application questions ("Your fit for the role," "Your values/goals," "Why Modulate?"), focus on relevant experience and motivations

  • Avoid including protected demographic information

  • Keep responses authentic and in your own voice

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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