Salary
💰 $170,000 - $215,000 per year
Tech Stack
AirflowBigQueryCloudDistributed SystemsDockerGoogle Cloud PlatformKubernetesPostgresPython
About the role
- Architect and lead the development of distributed services and infrastructure to support the entire machine learning/modeling lifecycle.
- Design and implement robust data pipelines for feature engineering and model training using tools like Airflow and Dataflow.
- Develop and maintain systems for deploying, serving, and monitoring ML models in production.
- Work closely with data scientists to translate modeling needs into robust, scalable engineering solutions.
- Drive technical design, specifications, and implementation for our backend modeling services.
- Take ownership of systems that build, train, and deploy models; design and build a scalable MLOps platform.
Requirements
- 5+ years of professional backend software engineering experience.
- Expert object-oriented programming understanding in Python
- Experience building distributed systems, particularly for MLOps or data processing workflows.
- Experience building and maintaining CI/CD pipelines, especially for ML models.
- You are an excellent communicator who can simplify complex problems and work collaboratively.
- You are comfortable making trade-offs between quality, complexity, and speed-of-delivery.
- Some technologies you will use: Cloud platform: GCP; Programming language: Python; Orchestration: Airflow; Data warehouse & databases: Postgres, BigQuery; Containerization: Kubernetes & Docker; Messaging system: Google PubSub