As a Software Engineering Intern, you’ll design and implement workflows for running Helical models at scale. You’ll work with technologies like Docker, Apache Airflow, Jupyterhub, MLflow, AWS, helping us improve the reliability, scalability, and observability of our machine learning pipelines.

You’ll collaborate closely with our AI infrastructure engineers to streamline how Helical’s Python-based modeling workflows are executed, monitored, and scaled in containerized environments.

Requirements

• Python proficiency, including scripting and automation for containerized and cloud-based workflows
• Experience with Docker and Docker Compose for developing, testing, and deploying multi-container applications
• Strong Linux skills, including shell scripting, process management, file systems, permissions, SSH key management, and resource monitoring
• Experience with monitoring and observability of systems and containers using Grafana and Prometheus
• Knowledge of Git and collaborative development workflows
• Familiarity with YAML/JSON for configuration and deployment
• Experience interacting with REST APIs using Python or curl
• Basic understanding of workflow orchestration tools (Apache Airflow) and Docker networking

Nice to Haves

• Experience deploying or scaling workloads on cloud platforms (AWS: ECS, EKS, EC2, S3)
• Experience developing frontend applications using Next.js and React
• Familiarity with Helm charts for packaging and deploying Kubernetes applications
• Strong debugging, documentation, and system-level thinking skills
• Interest in building developer-facing tools or improving operational workflows
• Security awareness: secure coding practices, least-privilege principles, environment variable management, safe handling of credentials and API keys