
Senior Data Scientist with LLM experience
- Toronto, ON
- Permanent
- Temps-plein
You will help design and implement data-driven solutions for complex business challenges by discovering, extracting, and modeling knowledge from large-scale natural language datasets. Your work will involve prototyping new ideas and collaborating with data scientists, product designers, data engineers, front-end developers, and domain experts to drive innovation.
This role offers the opportunity to work in a fast-paced, start-up-like culture while leveraging the resources and scale of an established company.Responsibilities
- Develop and implement LLM-based applications for various use cases.
- Evaluate and maintain data assets and training/evaluation datasets.
- Design and build pipelines for preprocessing, annotating, and managing large-scale text datasets.
- Collaborate with domain experts to understand requirements and ensure ML applications align with business needs.
- Conduct experiments and evaluate model performance to drive continuous improvements.
- Fine-tune and deploy large language models(LLMs) to enhance their performance on specialized tasks.
- Interface with other technical teams to finalize requirements.
- Work closely with development teams to understand complex product requirements and translate them into scalable software solutions
- Implement development best practices, including coding standards, code reviews, and production-ready implementations.
- Practical experience with large language models (LLMs), prompt engineering, fine-tuning RAG-based applications, and benchmarking using frameworks like LangChain.
- Strong background in natural language processing (NLP) with experience using spaCy, word2vec, Flair, BERT.
- Formal training in machine learning, including dimensionality reduction, clustering, embeddings, and sequence classification algorithms.
- Proficiency in Python and experience working with ML frameworks like PyTorch, TensorFlow, and Hugging Face Transformers.
- Experience with cloud platforms such as AWS, GCP, or Azure.
- Understanding of data modeling principles and complex data architectures.
- Experience working with relational and NoSQL databases and vector stores (e.g., MySQL, Postgres, Solr, Elasticsearch, OpenSearch).
- Familiarity with distributed computing frameworks like Spark, Scala, or Ray (highly preferred).
- Knowledge of API development, containerization (Docker, Kubernetes), and ML deployment (highly preferred).
- Hands-on experience with ML Ops/AI Ops, including experiment tracking tools like LangFuse and DVC.
- Experience with deep learning frameworks such as PyTorch, Tensorflow and Hugging Face Transformers
- MS in Data Science, Computer Science, Statistics, Machine Learning, or related field
- 5+ years of relevant work experience
Nous sommes désolés mais ce recruteur n'accepte pas les candidatures en provenance de l'étranger.