We appreciate your interest in Coveo. We will be in touch with you shortly.
Senior ML Ops Developer
- Province of Quebec (Canada)
- Machine Learning
- Full-time
- Remote or Hybrid
*Please note that we have 3 Senior Machine Learning Developer roles open hybrid, in Montreal and Quebec city locations, as well as remote across the Quebec and Ontario provinces.
Play a key role in shaping LLMOps best practices
As a Senior Machine Learning Developer on the ML Platform team, you will play a key role in supporting the teams of applied scientists responsible for creating and training Large Language Models (LLMs) and other ML models at scale.
Your primary responsibility will be to create and maintain a suite of tools 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
- Analyze and improve the performance of our models and ML Platform to help meet critical SLOs for training models at scale and low-latency inference.
- Facilitate the adoption and usage of ML platform and observability resources and provide guidelines to improve operational efficiency and service reliability.
- Engage with your community of peers to challenge the status quo, improve our shared ways of working, and influence overall architecture decisions.
- 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 5+ years of Machine Learning industry experience.
- You operationalized, instrumented and supported ML models in production at a non-trivial scale and you're ready to take on new challenges and deploy LLMs (if you haven't already!).
- You are fluent in good data and software engineering practices, and you are able to develop the tools and culture which enable ML teams to deliver reliable production code in an efficient manner.
- You enjoy collaborating with scientists on a daily basis to understand their pain points and figure out how to improve their tools and increase their efficiency. You also have experience working in cross-functional teams.
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 maintaining and evangelizing internal resources and libraries.
- You have acquired considerable 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 are recognized for your communication skills and presenting complex technical subjects to audiences with different levels of technical proficiency.
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.
Absolutely! This is a question women and under-represented groups ask themselves more often than the rest of the population. Don't underestimate yourself, we are not looking for someone perfect but for someone who is motivated, capable and who will thrive in this position. Allow us to discover you!
Coveo is a Quebec-based company, pioneer in AI-powered search and recommendations. Coveo uses AI technologies and intelligent search to personalize every digital experience for customers, partners, dealers, and employees. Coveo combines unified content, unified interactions behavioral data and machine learning to deliver relevant information and recommendations across every business interaction, making websites, e-commerce, contact centers and intranets efficient, effortless, content-rich, thus boosting conversion.
If it were easy, someone else would have done it. All of our colleagues at Coveo find the drive to continuously seek new challenges and test roads no one else has ever explored. This ethos has allowed us to become a world leader in an innovative industry and to create a collaborative, diverse and trusting place to work filled with amazingly talented and passionate people. We love a good challenge, and we never say no to an opportunity to learn and develop new cutting-edge skills. Discover our values here
In-person
This role requires you to be in the office full-time, whether it be at our Quebec, Montreal, Weert, or London locations. Our modern infrastructures are designed to enhance cross-team collaboration and promote overall well-being.
Hybrid
Our offices in Quebec City, Montreal, London and Weert are designed to foster collaboration and your well-being. We gather there on our pillar days two times a week to strengthen in-person interactions and encourage creativity, all while providing you with the flexibility of a hybrid environment.
Remote
We hire from all over the world because the diversity of backgrounds fuels our continuous innovation. Our benefits will enable you to work comfortably from home, but you may be required to travel to attend our in-person team-building events.