Middle to Senior ML Engineer

Role Description

You'll build and operate the data pipelines that power our AI systems — streaming, near-real-time, and batch. You'll work with high-volume structured and unstructured data on platforms like Spark and Databricks, building the infrastructure that connects raw data to production models across personalization, fraud, and GenAI use cases.

Responsibilities

• Build and maintain ML inference and feature engineering pipelines on Databricks
• Develop feature pipelines — transformations, aggregations, time-based features at scale using PySpark
• Deploy and manage models in production — versioning, registry, serving (MLflow)
• Build batch inference jobs that generate predictions at scale
• Integrate ML outputs with streaming infrastructure (Kafka) for downstream consumption
• Optimize SQL queries across multiple engines (Databricks SQL, PostgreSQL)
• Monitor data quality, pipeline reliability, and model serving health
• Collaborate with ML scientists to productionize their research

Qualifications

• 3+ years of professional Python development in a data or ML engineering context
• Strong PySpark experience — writing, debugging, and optimizing Spark jobs in production
• Hands-on experience with Databricks or similar managed Spark platform (EMR, Dataproc)
• Production experience with Kafka or equivalent streaming platform
• Solid SQL skills across multiple database engines
• Familiarity with ML model deployment and serving (MLflow, SageMaker, or equivalent)
• Familiarity with Kubernetes
• Understanding of feature engineering patterns and data pipeline design
• Strong analytical thinking and data intuition

Nice to have

• Exposure to recommendation systems or personalization platforms
• Experience with pipeline orchestration (Databricks Asset Bundles, Airflow, or similar)
• Familiarity with columnar processing libraries (Polars, pandas)
• Experience with ML observability — model performance monitoring, data drift detection, pipeline alerting
• iGaming domain experience

Benefits

• Work in a technically strong environment with modern stack and mature Agile culture
• High autonomy, decision-making authority, and close cooperation with leadership
• A position in a product development company with a dynamic environment and several concurrent projects
• Opportunity to contribute (your ideas for improvement implementation)
• Continuous self-improvement and growth, including budget for certifications and courses
• Competitive salary plus financial bonuses for performers
• Company prepaid AI agent
• Medical insurance coverage
• English language courses
• Wellbeing package: online-yoga classes, Yakaboo, BetterMe App: Health Coaching, BetterMe App: Mental Health
• Corporate events and fun team-building activities
• Remote-first culture