Our client, a cutting-edge technology firm at the forefront of AI innovation, is seeking a brilliant and ambitious AI Research Scientist specializing in Natural Language Processing (NLP). This exciting role offers a hybrid work arrangement, allowing for a blend of focused remote research and collaborative in-office sessions in Toronto, Ontario, CA . The successful candidate will be instrumental in pushing the boundaries of NLP, developing novel algorithms, and building state-of-the-art models that drive next-generation AI applications. You will contribute to impactful projects, from semantic understanding and machine translation to conversational AI and text generation. This position requires a deep theoretical understanding of machine learning and a passion for translating research into tangible, deployable solutions.
Key Responsibilities:
Conduct advanced research in Natural Language Processing, including areas such as deep learning for NLP, language models, sentiment analysis, entity recognition, and question answering. Design, develop, and implement novel NLP algorithms and machine learning models. Train, fine-tune, and evaluate large language models (LLMs) and other NLP systems. Collaborate with software engineers to integrate research findings and models into production systems. Stay abreast of the latest academic research and industry trends in AI and NLP. Publish research findings in top-tier conferences and journals. Contribute to the development of intellectual property and patents. Mentor junior researchers and engineers on NLP techniques. Analyze and interpret complex datasets for model training and evaluation. Present research findings and project progress to technical and non-technical stakeholders. Participate actively in research discussions and brainstorming sessions.
Qualifications:
Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related quantitative field. Proven track record of impactful research in NLP, demonstrated through publications, patents, or significant contributions to open-source projects. Strong theoretical foundation in machine learning, deep learning, and statistical modeling. Expertise in NLP techniques and libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers, spaCy, NLTK). Proficiency in programming languages such as Python. Experience with large-scale data processing and distributed computing environments (e.g., Spark). Excellent analytical, problem-solving, and critical thinking skills. Strong written and verbal communication skills, with the ability to articulate complex technical concepts clearly. Ability to work independently and collaboratively in a fast-paced, innovative environment. Experience with cloud platforms (AWS, Azure, GCP) is a plus. This role is ideal for a creative and driven researcher who thrives on tackling challenging problems and contributing to the future of artificial intelligence. The hybrid model encourages a dynamic approach to work.
