Canada
about 2 hoursData Science ML/GenAI Engineer
Remote, Canada (Québec and Eastern Canada preferred) | Openings: 1 | Employment Type: Direct Hire | Role Type: Backfill | Base Salary: CAD $80K–$120K
About Our Client
Our client is a growing SaaS company that builds cloud-based solutions for organizations managing critical infrastructure across North America. This role joins a product team building a stakeholder management platform for clients in mining, energy, renewable energy, and utilities.
About the Role
Our client is looking for a hands-on Data Science ML/GenAI Engineer to take over and build on GenAI work already in progress. The current project uses LLMs to evaluate, filter, and extract information from external text sources such as news articles and social media posts. You'll be the only person in this role on a small team, so autonomy and end-to-end ownership are essential.
Key Responsibilities
- Take over and evolve the existing GenAI work and codebase, deciding what should be preserved, improved, consolidated, or redesigned.
- Design, prototype, and evaluate LLM/NLP solutions to evaluate, filter, and extract information from news articles, social media posts, and other unstructured text.
- Build LLM-based agents and other GenAI applications, including text classification, entity extraction, semantic search, and summarization.
- Define and run rigorous evaluation of LLM outputs to confirm quality, performance, and production readiness.
- Explore, prepare, transform, and analyze data independently using Databricks.
- Turn successful prototypes into production-ready solutions using clean, modular, and well-tested code.
- Design and develop REST APIs that expose data, models, or analytical results to downstream applications.
- Collaborate with the data engineering and application development teams, including a team based in Europe.
Requirements
- 2 to 5 years of experience in data science, machine learning, or ML engineering.
- Practical, hands-on experience with LLMs and GenAI, including building LLM-based agents.
- Strong ability to evaluate LLM outputs rigorously and judge when a solution is ready for production.
- Hands-on experience with unstructured text data and NLP/LLM techniques such as RAG, embeddings and similarity search, hybrid search (BM25 + semantic), text deduplication, text classification, NER, re-ranking, and prompt engineering.
- Strong Python skills, including pandas, scikit-learn, and PyTorch.
- Production-quality code beyond notebooks: object-oriented programming, clean code, and automated testing.
- Strong data analysis and statistics skills.
- Hands-on experience with Databricks or a comparable data platform.
- Experience designing and developing REST APIs.
- Master's degree or equivalent professional experience in a related field.
- Strong written and verbal English.
- Must live in Canada and be authorized to work in Canada.
Nice-to-Have
- Hands-on experience deploying your own code to production, ideally at a software company.
- Familiarity with Agile methodologies, Git, and CI/CD practices.
- Experience with news, social media, or other large-scale unstructured text data.
- Experience in communications, public relations, or media.
- Familiarity with vector databases, RAG frameworks, and fine-tuning NLP models.
- Experience with MLflow or similar tools.
- Basic knowledge of TypeScript and Node.js.
- French proficiency.
Benefits
- Competitive salary based on experience and qualifications.
- Medical, dental, and vision insurance.
- Retirement plan with company contribution.
- Generous paid time off.
- Company-paid holidays.
- Flexible work options.
- On-call compensation for eligible on-call shifts.
AI Use in Hiring
As part of our hiring process, this role may use artificial intelligence or automated tools to assist with reviewing and screening applications. These tools support, but do not replace, human judgment in making hiring decisions.
Your application will only be counted once you complete the full registration process on the KeyStone platform, including creating your profile, uploading your CV, and submitting your application. The AI interview is optional and encouraged, but is not required for your application to be counted.
As part of our hiring process, this role may use artificial intelligence or automated tools to assist with reviewing and matching applications. These tools support, but do not replace, human judgment in making hiring decisions.
Please note that your application is only complete once you finish the registration process on the Keystone AI platform—including creating your profile, uploading your CV, and submitting your application. The AI interview is optional and encouraged, but it is not required for your application to be counted.
