MLOps Engineer

About us

Hear is an innovative early-stage startup dedicated to shaping the future of conversational intelligence. We are passionate about AI, technology, and addressing real-world challenges. We uphold high safety standards for our products and foster a collaborative environment with exceptional people.

About the role

At Hear, we’re seeking an experienced MLOps/DevOps Engineer to bridge the gap between model development and production. This role focuses on automating machine learning pipelines, deploying scalable infrastructure on GCP, and managing code through Atlassian Bitbucket, while ensuring robust monitoring with DataDog.

Responsibilities

• Design, implement, and maintain robust CI/CD pipelines for ML models and applications.
• Automate deployment and scaling processes using modern DevOps tools (e.g., Docker, Kubernetes, Terraform, Pulumi) on Google Cloud Platform (GCP).
• Integrate and support vLLM and others to optimize ML model deployment.
• Manage source code and version control using Atlassian Bitbucket.
• Implement and monitor performance metrics with DataDog, ensuring high availability and rapid incident response.
• Collaborate with data scientists and software engineers to integrate models into production workflows.
• Implement security best practices in the deployment process.

Requirements

• 3 years of experience with ML lifecycle management and modern DevOps practices.
• Proficiency in programming languages such as Python and shell scripting.
• Hands-on experience with GCP, container orchestration tools, and DataDog for monitoring.
• Familiarity with vLLM integration and Atlassian Bitbucket.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Strong problem-solving skills and the ability to work in a fast-paced environment.