Applied Machine Learning Scientist, NLP

POSITION SUMMARY

As an Applied ML Scientist, NLP, you will be at the forefront of developing and implementing cutting-edge advancements in language models and natural language processing systems, enabling impactful applications of the latest research breakthroughs. This role offers a unique opportunity to lead applied research that bridges the gap between state-of-the-art Large Language Models (LLMs), Small Language Models (SLMs), and practical applications across critical sectors such as health, industry, and responsible AI.

You will work alongside leading ML researchers, data scientists, and AI engineering teams to design and implement solutions powered by LLMs and SLMs with a focus on scalability, efficiency, and real-world impact. This role calls for research capability, AI engineering expertise, and deep knowledge in Natural Language Processing (NLP) to advance the use of frontier ML systems including open-source tools and robust architectures that accelerate Vector's mission.

The position encourages publishing applied research papers though the primary emphasis is on high-impact applications and real-world solutions. Candidates should have expertise in deploying ML systems including experience with the latest research and AI engineering approaches to optimize performance and enable flexible adaptable solutions. This role is an opportunity to lead and innovate in developing sophisticated NLP systems that push boundaries in technology and application.

KEY RESPONSIBILITIES:

• Research and implement state of the art NLP/Natural Language Understanding (NLU) techniques to solve real world problems;

• Work in collaboration with researchers, Applied ML Specialists, Vector's professional staff, and collaboration partners to build demos, minimum viable products (MVP), and prototypes;

• Provide scientific advice regarding overall machine learning application strategies and roadmaps;

• Provide scientific oversight for Vector-led or co-led efforts to prepare specific datasets for machine learning research;

• Serve as the lead Vector scientific contributor for health, industry, and responsible AI projects including contributing to or leading the authoring of peer-reviewed research papers;

• Contribute to training sessions and other initiatives for Vector staff and stakeholders that help increase AI knowledge and the capacity of the system to recognize and act on opportunities to apply machine learning;

• Serve as an expert and facilitate identification of experts among the Vector research community for external stakeholders (e.g., health and other sectors) to advise on machine learning research trends and applications; and,

• Other duties as assigned.

SUCCESS MEASURES:

• Successfully develop and deploy NLP models and applications, including Large and Small Language Models, that address real-world challenges in health, industry, and responsible AI.

• Make significant research engineering contributions by optimizing, scaling, and deploying high-performance NLP systems that demonstrate the latest advancements in machine learning.

• Collaborate effectively with internal teams and external partners to create impactful prototypes, demos, and MVPs that highlight the practical value of applied NLP.

• Contribute actively to training programs and knowledge transfer initiatives, enhancing ML literacy and capability across Vector and partner organizations.

• Provide thought leadership on emerging NLP trends and ML application strategies, aligning with and supporting Vector's strategic objectives and influencing broader research directions.

PROFILE OF THE IDEAL CANDIDATE:

• PhD degree in computer science or computer engineering with a research focus on NLP preferred.

• Demonstrated expertise in one or more of NLP or NLU application domain like speech recognition, text summarization, entity recognition, information retrieval and language generation.

• Demonstrated experience applying machine learning research to novel problems and data sets.

• Experience with software engineering and/or data engineering is considered an asset.

• Strong knowledge and experience of Python.

• Experience with parameter and architecture tuning of deep learning algorithms is considered an asset.

• Experience using open-source deep learning software frameworks (PyTorch, Tensorflow, JAX, or CUDA).
  
  

At the Vector Institute, we are committed to driving excellence and leadership in Canada's knowledge, creation, and use of AI to foster economic growth and improve the lives of Canadians. We strive for greater inclusion in the programs and culture that we build by welcoming and encouraging applications from all qualified candidates. This includes but is not limited to applicants who are Indigenous, 2SLGBTQIA+, racialized persons/visible minorities, women, and people with disabilities.

If you require an accommodation at any point throughout the recruitment and selection process, please contact hr@vectorinstitute.ai and we will happily work with you to meet your needs.