Software Engineer, Data Science (Python, AWS)
Overview
Own the engineering backbone for machine learning and data science initiatives at a Naperville-based organization. You will build reliable foundations for Python-based modeling workflows while partnering with infrastructure and data teams. This contract role focuses on strengthening platform capabilities and delivery practices. What sets this apart: direct ownership of ML infrastructure in a collaborative, cross-functional environment.
What You'll Do6
- 1Build and scale Python-based services that power machine learning workflows, ensuring low-latency and reliability.
- 2Design CI/CD pipelines with GitHub Actions and Docker to automate testing and deployment of data science code.
- 3Debug production issues in distributed systems using Kubernetes and Prometheus, reducing downtime.
- 4Partner with data engineers to integrate Spark and Airflow pipelines, enabling seamless data flow.
- 5Ship internal tools that improve model versioning and experimentation tracking using MLflow.
- 6Drive adoption of infrastructure-as-code with Terraform to manage cloud resources on AWS.
Requirements6
- 13+ years building production software with Python and SQL.
- 22+ years deploying and managing containers with Docker and Kubernetes.
- 3Hands-on experience with cloud platforms, specifically AWS services like S3 and Lambda.
- 4Proficiency in CI/CD tools such as Jenkins or GitHub Actions.
- 5Familiarity with data processing frameworks like Spark or Pandas.
- 62+ years working with relational databases and writing optimized queries.
Salary Insight
$51 - $60k per year
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