Senior Machine Learning Engineer

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. #J-18808-Ljbffr