Senior Machine Learning Engineer / Machine Learning Scientist (Fraud Detection)
USA Remote | $160,000 to $210,000 base + bonus + equity
This is a high-impact opportunity to work on machine learning systems that directly influence real-time financial decisions at scale. You will take ownership of experimentation and production models that sit at the heart of a fraud prevention platform, with the autonomy to shape how models are built, evaluated, and deployed.
The Company
They are a well-established fintech business operating at global scale, providing AI-driven fraud protection for e-commerce transactions. Their platform enables online retailers to approve more genuine customers while protecting against fraudulent activity, backed by a financial guarantee model. With a strong international presence and a customer base spanning thousands of merchants, they process large volumes of transactions across multiple markets. Machine learning is central to their product, with continued investment in their in-house ML infrastructure and experimentation capabilities.
The Role
- Own end-to-end machine learning development, from experimentation through to production deployment and monitoring
- Design and implement scalable ML pipelines to support fast, high-quality experimentation
- Develop and improve fraud detection models, including ensemble approaches and decision systems
- Build robust offline evaluation frameworks to validate model performance before release
- Collaborate with product, engineering, and risk teams to translate business challenges into ML solutions
- Contribute to best practices across model development, testing, and monitoring
Your Skills & Experience
- Strong commercial experience in machine learning, with a solid grounding in statistics and model evaluation
- Proven ability to design and run experiments and translate findings into production systems
- Experience working in distributed computing environments, including Spark
- Proficiency in Python and SQL, with experience building scalable data and ML pipelines
- Deep understanding of supervised and unsupervised learning techniques in high-scale environments
- Ability to own complex problems end to end and deliver measurable business impact
What They Offer
- Base salary between $160,000 and $210,000, depending on location and experience
- Annual bonus up to 10% and a stock option package
- Comprehensive benefits including healthcare, retirement plans, and wellbeing support
- Unlimited paid time off and a dedicated learning and development budget
- A collaborative, research-minded environment with strong technical standards and ownership
How to Apply
If you are interested in applying your machine learning expertise to high-impact fraud detection systems, please submit your CV to learn more.