MLOps Engineer

MLOps Engineer I—Research Team

QuillBot ● India (Remote)

About : QuillBot is an AI-powered writing platform on a mission to reimagine writing. QuillBot provides over 57 million monthly active students, professionals, and educators with free online writing and research tools to help them become more effective, productive, and confident. The QuillBot team was built on the idea that learning how to write and use that knowledge is empowering. They want to automate the more time-consuming parts of writing so that users can focus on their craft. Whether you're writing essays, social media posts, or emails, QuillBot has your back. It has an array of productivity-enhancing tools that are already changing the way the world writes

What Will You Do?

• Collaborate with experienced data scientists and software engineers to gain insights into building scalable and efficient data pipelines, model training, and deployment systems.
• Troubleshoot issues in the entire machine learning infrastructure, from Linux, Docker, and Kubernetes up to the highest levels of our ML stack. Resolve issues, improve system performance, and make our stack the best in the industry.
• Assist in the design and development of on-premises MLOps solutions under the guidance of senior team members to support the delivery of machine learning models.
• Drive and uphold high engineering standards, bringing consistency to codebases encountered and ensuring software is adequately reviewed, tested, and integrated.
• Convert offline models built by researchers into real machine learning production systems.
• Optimise existing models for better performance and throughput.
• Incorporate ML model training, validation, and evaluation settings in addition to traditional coding tests like unit and integration testing.
• Build and maintain tools for deployment, monitoring, and operations.
• Receive mentoring from senior members of the team to grow your skills and expertise in MLOps and related areas.
• Continuously refine and enhance CI/CD workflows to support the evolving needs of the machine learning infrastructure.

Ideal Candidate

• Recent graduate of a degree program in Computer Science, Software Engineering, Data Science, or a related field.
• Basic programming skills in a modern programming language (Java, Scala, Python, Kotlin).
• Understanding of the MLOps life cycle and experience with MLOps workflows
• Experience with tools & practices of the trade, such as Kubernetes, GCP/AWS/Azure, CI/CD, common ML frameworks, and data management.
• A keen interest in machine learning engineering and a willingness to explore how it can be scaled effectively.
• Strong desire to learn and good communication skills, with an enthusiasm for collaborative problem-solving.