Python/NLP Developer

3 weeks ago

Montreal, Canada Alteo Inc. Full time

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:

- DEC/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.

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