Key skills
Machine Learning EngineeringData EngineeringBackend Software EngineeringPythonSQLFull Modern Data StackOLAP / OLTP Data ModellingKey-Value StoresStreaming Data PipelinesAPI FrameworksProduction ML ServiceFull-Stack DevelopmentSoft SkillsTypeScriptHaskellAIMachine LearningMLSnowflakeKafkaAirflowdbtFivetranReactFastAPIFlaskDynamoDBKinesisRedis
About this role
Mercury is a fintech company committed to crafting an exceptional banking experience for startups. The Senior Machine Learning Engineer will partner with data science and engineering teams to design and deploy ML and Gen AI microservices, focusing on automating reviews and enhancing the overall review experience.
Responsibilities:
- Partner with data science & engineering teams to design and deploy ML & Gen AI microservices, primarily focusing on automating reviews
- Work with a full-stack engineering team to embed these services into the overall review experience, including human in the loop, escalations, and feeding human decisions back into the service
- Implement testing, observability, alerting, and disaster recovery for all services
- Implement tracing, performance, and regression testing
- Feel a strong sense of product ownership and actively seek responsibility – we often self-organize on small/medium projects, and we want someone who’s excited to help shape and build Mercury’s future
Requirements:
- 7+ years of experience in roles like machine learning engineering, data engineering, backend software engineering, and/or devops
- Expertise with a full modern data stack: Snowflake, dbt, Fivetran, Airbyte, Dagster, Airflow
- SQL, dbt, Python
- OLAP / OLTP data modelling and architecture
- Key-value stores: Redis, dynamoDB, or equivalent
- Streaming / real-time data pipelines: Kinesis, Kafka, Redpanda
- API frameworks: FastAPI, Flask, etc
- Production ML Service experience
- Working across full-stack development environment, with experience transferable to Haskell, React, and TypeScript