Senior Nlp Engineer
Behavox
Toronto
- AI-powered communication features: Use existing NLP technologies and AI solutions, including LLMs, to develop communication assistance features and risk-detection capabilities for clients.
- Data science and model development: Design, train, fine-tune, and evaluate NLP models, and take them from prototype to production with MLOps and engineering.
- Database design and development: Design, develop, and maintain the databases behind our NLP pipelines, and develop and implement a strategic blueprint for deploying databases across the organization.
- Data administration and testing: Develop and implement data administration policies, standards, and models. Test data models and database management systems before and after release.
- Infrastructure improvement: Collect data to identify areas for improvement in the organization’s IT and data infrastructure, and turn findings into practical changes.
- Documentation and reporting: Document reporting needs, queries, logic, results, and recommendations for other information systems professionals.
- Collaboration and mentoring: Advise product and engineering teams, explain model behaviour to clients alongside the revenue team, and mentor other engineers through Git-based workflows and code review.
- Education: Master’s degree in computer engineering or a related field (such as computer science, computational linguistics, or machine learning).
- Experience: 5 or more years of experience building NLP, data science, or machine learning systems, including solutions shipped to production.
- Language: English.
- NLP and AI: Hands-on experience with transformer models and large language models (LLMs), including fine-tuning, retrieval-augmented generation (RAG), and embedding-based search, and with core tasks such as text classification, entity recognition, and relationship extraction.
- Data science: Experience building evaluation datasets and metrics, working with limited and imbalanced data, and explaining model behaviour to non-specialists.
- Databases and data modelling: Experience designing, developing, and testing databases, data models, and database management systems.
- Programming: Strong Python; working knowledge of C, C++, Go, Java, and JavaScript; daily use of Git.
- Production engineering: Experience serving, monitoring, and maintaining models and data systems in production on cloud platforms (AWS or GCP).
- Personal suitability: Accurate, organized, and detail-oriented, with sound judgment, initiative, and accountability. Adaptable, a quick learner, and a team player with a strong client focus and excellent written and oral communication.
- Salary: $170,000 to $230,000 CAD per year, depending on experience.
- A benefits package that includes an equity award aligned with long-term value creation, in addition to cash compensation.
- 30 days of paid time off annually, plus public holidays and sick leave.
- A hybrid role based in our modern Toronto office (1 day per week in office).
- The opportunity to work on a global, mission-critical AI platform alongside highly skilled engineers and technologists across multiple geographies.
- Real ownership and impact, building complex systems at scale in an environment that values speed, experimentation, and technical excellence.
- Initial conversation: We cover salary, location, core experience and skills, and values alignment.
- Technical interview: A deep dive into the technical competencies critical to the role.
- Behavioural interview: A deep dive into behavioural competencies.
- Practical task: The most aligned candidates complete a work simulation, typically presented and discussed with a group of colleagues and managers.
- Leadership meetings: You meet several of our senior leaders so you can make a fully informed decision.
- We want a genuine conversation, so the use of AI tools or assistance during live interviews is not permitted and will result in disqualification from the process.
- Interviews may be recorded for internal review, to support fairness and collaborative hiring discussions within the team.
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