Intermediate Developer - MLOps

Montreal (Province of Quebec, Canada)

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*Please note that we have 3 Senior Machine Learning Developer roles open hybrid, in Montreal and Quebec city locations, as well as remote in the Quebec province. 

Play a key role in shaping MLOps best practices 

As a developer on the ML Platform team, you will work on a suite of tools to support the teams of applied scientists in deploying, orchestrating and productionalizing ML models at scale. 

Your primary responsibility will be to create and maintain tooling, libraries and workflows that enable the efficient development of robust, scalable, and maintainable ML models. You will also work closely with Applied Scientists to accelerate the iteration and experimentation process, ensuring faster and more effective model development.

Here is what makes this opportunity exciting:

The ML unit at Coveo focuses on finding ways to apply the latest advances in Recommender Systems, Ranking Optimization, LLMs and NLP to build innovative solutions in e-commerce, self-service and other business verticals.

We solve real problems with real data, for hundreds of large enterprise clients all around the world, on a modern platform that serves over 100M requests and automatically trains thousands of ML models on a daily basis.

Here is a glimpse at your 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

Here is what will qualify you for the role: 

  • 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

Here is what will make you stand out:

  • 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 

Do you think you can bring this role to life? 

You don’t need to check every single box; passion goes a long way and we appreciate that skillsets are transferable.
Send us your CV, we want to get to know you! Join the #Coveolife!

We encourage all qualified candidates to apply regardless of, for example, age, gender, disability, gaps in CV, national or ethnic background. We know that applying for a new role is a lot of work and we really appreciate your time.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: AWS DevOps E-commerce Engineering Kubernetes LLMs Machine Learning ML models MLOps NLP Pipelines Python PyTorch Recommender systems Snowflake Terraform Testing

Region: North America
Country: Canada

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