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Python/NLP Developer [#4877]Alteo Inc. • Montreal, Montreal (administrative region), CA
Python / NLP Developer [#4877]
Alteo Inc. • Montreal, Montreal (administrative region), CA
Il y a plus de 30 jours
Type de contrat
- Permanent
Description de posteDEC / BAC in IT, Software Engineering or equivalent 3+ years of relevant experience. Professional experience in machine learning (ML) and natural language processing (NLP), best practices in experimentation and optimization, MLFlow, etc. Knowledge of modern language models (LLM), how they work, and how they are used via prompting (prompt engineering) or fine-tuning. Experience in Python (and / or Java) programming in a data processing and AI context. Proficiency in common tools and libraries : LLM APIs for text completion with function calls (tool use), streaming, “chain of thoughts,” structured outputs, etc. Understanding of classic and modern information retrieval (IR) methods, including TF-IDF, BM25, dense retrieval, RAG, etc. Familiarity with collaborative software development tools : Git, CI / CD, containers, etc. Ability to independently set up reproducible experiments (experimentation, A / B testing, performance logging, etc.). Experience with large-scale production systems or microservice-oriented architectures (an asset). Interest in conversational interfaces and intelligent assistants (an asset). Tech stack : AWS infrastructure : EC2, ECS Fargate, RDS, S3; GitHub, Jenkins, SonarQube, Jira, and Confluence cloud; Windows, Linux, and MacOS work environments.
Alteo is looking for a Python / NLP Developer for a permanent position based in Montreal.
Responsibilities :
- Maintain and implement new features in our search engine.
- Develop and maintain a click analytics system to learn user preferences.
- Design and improve an intelligent search assistant based on LLM models to assist users with their queries.
- Optimize the backend systems responsible for processing data and enriching the AI models used in search.
- Collaborate with NLP researchers, data scientists, and domain experts to experiment, test, and continuously improve our systems.
- Participate in benchmarking campaigns to measure performance (accuracy, recall, response time, etc.) and optimize systems based on the results obtained.
- Explore, design, and evaluate new approaches in NLP, such as prompt optimization, reinforcement learning, or hybrid symbolic / neural approaches.
Profile :
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Developer • Montreal, Montreal (administrative region), CA
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