Senior Machine Learning Engineer
Skills
Apache KafkaApache SparkAzure DatabricksContinuous ImprovementCost EfficiencyData ScienceECS
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 5+ years in Data Science Machine Learning or MLOps Engineering
- 3+ years consulting experience
- Strong Python and MLOps platform engineering background
- Deep AWS knowledge including ECS EC2 DynamoDB IAM and KMS
- Terraform experience
- Hands-on Databricks PySpark Delta Lake Unity Catalog and MLflow
- Kafka and Spark Structured Streaming experience
- Proven production ML model deployment and operations experience
- Ability to work independently in low-latency high-availability environments
Nice to have
- Seasoned consultant
- Independent worker
- Low-latency mindset
- High-availability mindset
Day to day
- Enhance and scale a real-time ML platform for fraud detection in high-volume payment environments.
- Develop feature store capabilities with online/offline parity and self-service data workflows.
- Build and maintain streaming data pipelines and robust model deployment processes with strong observability.
Hiring process
- Apply with your latest CV
- Shortlisted candidates will be contacted