Senior Machine Learning Engineer

How you’ll make an impact

• Build systems for training, deploying and monitoring machine learning models used in our Disputes platform, at scale
• Build and optimize data pipelines and backend services to process dispute and payment data in real time
• Build and scale our feature store for use‑cases both online and offline
• Take complete ownership of delivering comprehensive, end‑to‑end features within a startup‑like setting, driving the entire lifecycle from requirement refinement, data pipeline construction and model training to troubleshooting and production deployment
• Turn raw data into production‑ready features that feed our dispute systems
• Collaborate with platform and backend engineers to integrate models seamlessly

Experience and qualifications

• 5+ years of experience as MLOps /ML Engineer
• High proficiency in writing clear, production‑ready Python code
• Experience with production ML models (online or offline) and standard MLOps practices
• Experience with monitoring and observability of production systems, with a strong sense of ownership
• Experience with training and operating models on Databricks
• Familiarity in Cloud‑based application development (we use AWS & Azure)
• Familiarity with one or more ML frameworks and technologies: scikit‑learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, Triton
• Strong communication skills, able to express ideas clearly and collaborate across teams

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