Applied Machine Learning Specialist

Vector Institute•Toronto, ON

1d•CA$100,600 - CA$125,800•Hybrid

About The Position

As an Applied Machine Learning Specialist, you will contribute to developing reusable software to apply and scale research breakthroughs in machine learning and AI. You will collaborate with some of the best and brightest AI engineering team members and data scientists at Vector and leading industry and health organizations. You will also collaborate with some of the best and brightest machine learning researchers.

Requirements

Bachelor's degree in computer science, mathematics, electrical engineering, or related discipline;
2+ years of experience in machine learning, developing, and deploying predictive models and optimizing algorithms;
Experience applying machine learning research to novel problems and data sets;
Demonstrated experience in machine learning and/or statistics;
Demonstrated data engineering background working with messy real-world data;
Demonstrated analytical skills to identify signal in data and feasibility of prediction;
Knowledge and experience of Python and preferably C/C++ and C#;
Experience leading technical scope for multiple projects;
Experience working with interns and guiding their work for achieving deliverables;

Nice To Haves

Master's degree preferred;
Software engineering background with experience in production deployment is preferred;
Experience working on teams that land high-quality software successfully in production is preferred;
Experience with parameter and architecture tuning of deep learning algorithms is preferred;
Experience in leading open-source deep learning software frameworks (PyTorch, TensorFlow, CUDA) is preferred;
User interaction/design expertise with Human-Computer Interaction (HCI) engineering is considered an asset.

Responsibilities

Deliver software and models for AI development projects following an agile methodology with teams that can include Vector Applied ML Specialists, Applied ML Scientists, professional staff, researchers, graduate students, and industry sponsors;
Design and develop reference applications and model templates that apply AI research to real-world problems using public and private data sets, providing software for training, testing, operating, and updating models;
Design, develop, and contribute to open-source software that applies AI research techniques to common problems;
Mentor sponsor AI engineering team members and student researchers on industry collaboration projects that apply AI research to shared problems, mentoring on engineering best practices, and assisting with operational issues;
Develop prototypes and proofs of concept;
Report and present software development outcomes for team efforts including demos, status, and results;
Lead interns and manage their scope of work;
Act as technical lead for multiple projects and deliver projects in collaborative settings; and,
Other related duties as assigned from time to time.