Release Engineer

• Manage the end-to-end release process of machine learning algorithms and infrastructure components, from qualification through deployment.
• Validate and test new algorithm releases to ensure they meet performance, stability, and compliance standards.
• Create and execute deployment plans across various environments (staging, production), ensuring minimal risk and downtime.
• Collaborate closely with AI researchers, MLOps, and software engineers to understand release requirements, share feedback, and resolve pre-release issues.
• Identify and drive automation opportunities within the release pipeline to improve efficiency, reliability, and traceability.
• Oversee updates to infrastructure components, ensuring compatibility and performance across systems.
• Monitor deployments, proactively identify issues related to model behavior or infrastructure anomalies, and drive resolution with relevant teams.
• Maintain clear and accurate release documentation, including version history, deployment notes, and incident reports.

• Bachelor's degree in Computer Science, Software Engineering, or industry equivalent.
• 2+ years of experience in QA & Automation
• Proficiency in scripting languages (e.g., Python, Bash).
• Experience with containerization technologies (e.g., Docker, Kubernetes).
• Familiarity with CI/CD pipelines (e.g., GitLab CI/CD, Jenkins).
• Experience with cloud platforms (e.g., AWS, GCP).
• Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.

• Strong understanding of the machine learning lifecycle, from experimentation to deployment and monitoring.
• Experience with specific MLOps platforms or tools.
• Experience in a fast-paced startup environment.

• Develop an...

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