We are looking for a data ML engineer to join our team in New York City. This is an exciting role at a rapidly growing start-up, where you will be working with an exceptional team to design and build scalable systems to support our predictive models.
You'll be working on:
- Helping architect our data infrastructure to help define product success
- Building and deploying across the entire process of data extraction, transformation, matching, and exploration for successful machine learning modeling, testing and deployment
- Building machine learning models for client consumption
- Setting-up ETL python pipelines that processes billions of unstructured/structured data points
- Contributing to infrastructure reliability and scalability
- Ensuring data security, including via appropriate access control mechanisms, a stringent secure-by-design mindset, and following industry best practices
- Managing the data team’s infrastructure, including databases, computing resources, and orchestration
- Building large-scale batch and real-time data pipelines with data processing frameworks (e.g. Airflow, Spark, EMR, etc)
- Helping drive optimization, testing, and tooling to improve data quality
- Experience with distributed systems, distributed data stores, data pipelines, and other tools in the Relational and Big Data ecosystems
- Experience with AWS infrastructure
- Experience with developing and scaling of production systems.
- Experience with python, Postgres and TypeScript