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Mid-Senior ML Engineer
Suntech InnovationML Engineer responsible for building and operating data pipelines for AI systems in iGaming. Working with structured and unstructured data on platforms like Spark and Databricks.
Tech Stack
Tools & technologiesAirflowKafkaKubernetesPandasPostgresPySparkPythonSparkSQL
About the role
Key responsibilities & impact- 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.
- 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
Requirements
What you’ll need- 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
Comp & perks- 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.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonPySparkSQLMLflowKafkaDatabricksfeature engineeringdata pipeline designpipeline orchestrationmodel deployment
Soft Skills
analytical thinkingdata intuitioncollaboration