Staff Software ML Engineer - R12079 at Oportun

Oportun is seeking a Staff Software ML Engineer to design and build self-serve platforms that combine real-time ML deployment and advanced data engineering capabilities. The ideal candidate will have a strong background in designing and implementing data platforms to enable self-serve for ML pipelines, while also enabling seamless deployments supporting real-time feature computation and prediction. This role involves building platforms similar to Michelangelo or Metaflow.

Responsibilities:

• Design and build self-serve platforms for real-time ML deployment and data engineering workflows.
• Develop microservices using Kubernetes and Docker.
• Create APIs and backend services using Python and FastAPI.
• Architect platforms for real-time ML inference using AWS SageMaker and Databricks.
• Build and optimize ETL/ELT pipelines using PySpark and Pandas.
• Design and implement robust CI/CD pipelines using Jenkins and GitHub Actions.
• Create and maintain technical documentation.
• Collaborate with cross-functional teams using Agile processes.

Requirements:

• 10-15 years of experience in platform engineering, backend engineering, DevOps, or data engineering.
• 5+ years of experience as architect building platforms that scale.
• Hands-on experience with real-time ML model deployment and data engineering workflows.
• Strong expertise in Python and experience with Pandas, PySpark, and FastAPI.
• Proficiency in Kubernetes and Docker.
• Advanced knowledge of AWS services like SageMaker, Lambda, DynamoDB, EC2, and S3.
• Experience building and optimizing distributed data pipelines using Databricks and PySpark.
• Understanding of databases such as MongoDB, DynamoDB, MariaDB, and PostgreSQL.
• Proficiency with CI/CD tools like Jenkins and GitHub Actions.
• Hands-on experience with observability tools like New Relic.

Oportun offers:

• A differentiated experience of being part of a team that fosters a diverse, equitable and inclusive culture.