Intermediate Developer - MLOps

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Coveo

πŸ“Remote - Canada

Job highlights

Summary

Join Coveo's ML Platform team as a Senior Machine Learning Developer and play a key role in shaping MLOps best practices. You will build and maintain tools supporting applied scientists in deploying and productionalizing ML models at scale. Your primary responsibility is creating and maintaining tooling, libraries, and workflows for efficient ML model development. You'll collaborate with applied scientists to accelerate model development. This role involves working with cutting-edge technologies in recommender systems, ranking optimization, LLMs, and NLP to solve real-world problems for enterprise clients. The position offers the chance to learn and evolve a modern tech stack, including Python, AWS, Kubernetes, and more. Coveo encourages applications from all qualified candidates.

Requirements

  • You have 3+ years of machine learning or software development experience
  • You have operationalized and supported ML systems or models in production
  • You are fluent in good software engineering practices

Responsibilities

  • Provide end-to-end ML tooling from data exploration to production deployment tooling
  • Facilitate development, deployment, automated testing, monitoring and debugging of ML models
  • Evaluate and integrate industry latest ML tools and technologies to provide a best-in-class ML development experience to our team of Applied Scientists
  • Learn and evolve our modern tech stack which includes Python, AWS, Kubernetes, Pytorch, Terraform, Snowflake, Honeycomb and others

Preferred Qualifications

  • You master best practices in MLOps, ML engineering, and large-scale deployment of ML models
  • You have experience developing, maintaining and evangelizing internal resources and libraries
  • You have acquired MLOps experience hosting models at scale, by previously building tooling to facilitate data exploration and experimentation as well as automating and orchestrating complex and efficient training pipelines
  • You have experience with DevOps practices, working with infrastructure-as-code and container technologies

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