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Coveo

Senior Applied Scientist

Montreal, QC, Canada

Full-time

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Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Apr 25, 2027
Experience: At least 4 years of industry experience applying NLP to production systems.
Posting language: English
Posted: Oct 27, 2026

Original job description

Shape the future of enterprise AI technology

Do you want to turn cutting-edge natural language processing into products impacting millions of users? As a Senior Applied Scientist in the Product Engineering group, you will help build the language technologies at the core of our AI products.

You’ll be contributing directly to the design, evaluation, and implementation of advanced AI solutions at the intersection of Retrieval Augmented Generation (RAG), information retrieval, semantic search, question answering, and agentic systems, always with real-world constraints in mind.

As one of our Senior Applied Scientists (NLP), you will:

Design, develop, and optimize modern language-based AI solutions, from data and modeling choices to evaluation strategies and production constraints and guardrails.
Apply and serve transformer-based language models at scale, delivering reliable, real-time experiences to enterprise users.
Collaborate closely with machine learning developers and the machine learning platform team to accelerate research and innovation cycles.
Contribute to research and development processes that foster efficiency, rigor, and a culture of applied science excellence.
Mentor junior applied scientists, supporting their growth and helping raise the overall level of expertise within the group.
Promote promising research and best practices in our applied science community.
Share our innovations externally through technical blog posts, presentations, or other thought leadership content.

Here is what will qualify you for the role:

At least 4 years of industry experience applying NLP to production systems.
Demonstrated skill in evaluating and improving LLM-based systems: building test sets, defining offline and online metrics, using LLM-as-judge methods with awareness of their limits, and catching regressions in non-deterministic systems.
Strong Python skills and fluency with typical tools (HuggingFace, Pandas/Polars, MLFlow), with the habit of writing tested, maintainable code that runs in production.
Familiarity with cloud infrastructure environments for Machine Learning such as AWS, Azure or GCP.
Experience working with AI coding assistants in your own development workflow, and a point of view on where they help and where they don’t.
Proven ability to collaborate effectively with other functions: You can clearly explain scientific risks and technical tradeoffs to Product Managers, Designers, and Software Developers.

What will make you stand out:

Experience building agentic systems: tool use, multi-step planning, orchestration, guardrails, and especially how you evaluated them and handled failure modes.
Familiarity with traditional lexical and linguistics-based approaches, including classical Information Retrieval and Search
Experience with the safety and trust side of enterprise AI, such as data governance and legal compliance
International work experience and a demonstrated ability to collaborate across cultures and perspectives.

Do you think you can bring this role to life?

Join the Coveolife!

We encourage all qualified candidates to apply regardless of, for example, age, gender, disability, gaps in CV, national or ethnic background.

This job description was written by humans, assisted by AI. We may leverage technology in our hiring process to help us see the person behind the resume.

Coveo is committed to providing accessible employment practices. If you require accommodation due to a disability at any point during the recruitment process, please contact HR@Coveo.com to discuss your needs.

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More about this job

Responsibilities

Design, develop, evaluate, and optimize production-ready language AI solutions, including RAG, semantic search, question answering, and agentic systems, while addressing reliability, real-time performance, and guardrails. Collaborate with machine learning and platform teams, mentor junior scientists, improve applied science practices, and share innovations through external technical content.

Requirements

Requires at least four years of industry experience applying NLP in production, strong Python and experience with tools such as Hugging Face, Pandas or Polars, and MLflow, plus familiarity with AWS, Azure, or GCP. Candidates should be skilled in evaluating LLM systems and communicating technical tradeoffs across functions; experience with agentic systems, information retrieval, enterprise AI safety, or international collaboration is an advantage.

Skills

Natural Language Processing
Retrieval-Augmented Generation
Information Retrieval
Semantic Search
Question Answering
Agentic Systems
Transformer-Based Language Models
Python
Hugging Face
Pandas
Polars
MLflow
Cloud Machine Learning Infrastructure
Production Machine Learning
AI Coding Assistants

Visa sponsorship

Not detected in the job text

Keywords

Natural Language Processing
Retrieval-Augmented Generation
Information Retrieval
Semantic Search
Question Answering
Agentic Systems
Transformer-Based Language Models
Large Language Models
Offline Metrics
Online Metrics
LLM-as-Judge
Regression Testing
Python
Hugging Face
Pandas
Polars
MLflow
AWS
Azure
Google Cloud Platform
AI Coding Assistants
Classical Information Retrieval
Search
Data Governance
Legal Compliance
Guardrails
Tool Use
Multi-Step Planning
Orchestration
Production Systems

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