Skip to main content
Tallo logoTallo logo
Apply for this opportunity

This job application is on an outside website. Be sure to review the job posting there to verify it's the same.

Senior Machine Learning Engineer

Job

Harnham

Remote

$175,000 Salary, Full-Time

Posted 3 days ago (Updated 13 hours ago) • Actively hiring

Expires 7/23/2026

Review key factors to help you decide if the role fits your goals.
Pay Growth
?
out of 5
Not enough data
Not enough info to score pay or growth
Job Security
?
out of 5
Not enough data
Calculating job security score...
Total Score
100
out of 100
Average of individual scores

Were these scores useful?

Skill Insights

Compare your current skills to what this opportunity needs—we'll show you what you already have and what could strengthen your application.

Job Description

Senior Machine Learning Engineer at Harnham Senior Machine Learning Engineer at Harnham in Franklin Park, Illinois Posted in about 4 hours ago.
Type:
full-time
Job Description:
Senior Machine Learning Engineer Remote in US $160,000 - $190,000 Base + 10% Bonus
THE COMPANY
Harnham is partnering with a fintech that has built a leading fraud protection platform enabling merchants to grow confidently by eliminating fraud and delivering frictionless customer experiences. They're a global company that processes billions of transactions annually, leveraging advanced machine learning to approve more good orders while protecting revenue. The company combines cutting-edge technology with a deeply collaborative and mission-driven culture. Their Machine Learning team sits at the core of the product, building and maintaining the models and experimentation frameworks that power fraud detection at scale.
RESPONSIBILITIES
Own the end-to-end lifecycle of machine learning projects, from experimentation through deployment and production monitoring. Build, maintain, and optimize production-grade machine learning models for fraud detection. Design and implement scalable ML pipelines to enable rapid experimentation and model iteration. Develop advanced feature engineering and statistical methodologies to improve model performance. Collaborate with Product, Engineering, and Risk teams to translate business needs into ML solutions. Contribute to model training, evaluation frameworks, and experimentation infrastructure. Ensure robustness, scalability, and reliability of ML systems in high-volume production environments. Drive best practices in testing, documentation, and model monitoring across the ML team.
SKILLS AND EXPERIENCE
4-6+ years of experience in machine learning within production environments. Strong foundation in machine learning theory, statistical modeling, and evaluation techniques. Experience building and deploying supervised and unsupervised ML models at scale. Proven track record of taking ML projects from research/prototype to production. Proficiency in Python, SQL, and key machine learning libraries. Experience working with distributed data processing tools such as Spark. Strong communication skills, with the ability to explain technical insights to non-technical stakeholders. Detail-oriented mindset with a focus on delivering measurable business impact.
PREFFERED EXPERIENCE
Experience in fraud detection, fintech, payments, or e-commerce domains. Advanced degree (Master's or PhD) in a quantitative field. Passion for writing well-tested, production-quality code. Interest in adversarial machine learning and combating fraud at scale.
BENEFITS
The compensation package includes a competitive base salary, performance-based bonus, and a comprehensive benefits package within a fast-growing, mission-driven organization.
HOW TO APPLY
Please submit your CV via the Apply link on this page to register your interest.
KEY TERMS
Machine Learning | Fraud Detection | Fintech | Payments | E-Commerce | Python | SQL | Spark | Data Science | Statistical Modeling | Feature Engineering | MLOps | Experimentation | Adversarial ML | Production ML Systems