Now Hiring: Associate Machine Learning Scientist

“Are you passionate about solving real-world problems with advances in machine learning?

Do you like working in the intersection of ML and driving its application to various domains?

Do you like large temporal datasets and think out of the box for novel solutions?

Then this is the right opportunity for you. The advanced technology team works on some of the most complex problems in applied machine learning. I am looking to add an Associate Machine Learning Scientist to the team who is enthusiastic about solving a unique challenge in the energy domain using machine learning. ”

- Talat Iqbal Syed, Product Lead, Advanced Technology

Job Description

The Associate Machine Learning Scientist (AMLS) serves as a key member of the team and an active participant in maintaining Amii's reputation for scientific excellence and providing insight in their area of expertise.

The AMLS uses their scientific knowledge and applied research experience to direct the research and development efforts of Amii Industry Partners and Clients. They bridge the gap between business opportunities and ML techniques, providing scientific oversight on technical projects. They will work with Amii’s industrial partner on defining and refining machine learning projects and deliver on the project through iterative stages of the Machine Learning Process Lifecycle (MLPL). This includes making informed decisions about data requirements, literature surveys on potential methodologies, advanced modelling techniques and evaluation.

They will work closely with the rest of the team, including researchers, research scientists and lead scientists and collaborate to find innovative solutions to the business problem. They will support Amii's internal teams as subject matter experts based on their technical specialties and applied Machine Learning experience.

The role focuses on achieving excellence in two main accountabilities:

  • Industry Engagement (working with Amii industrial partners to advance their ML projects and capabilities)
  • Stakeholder satisfaction (supporting Amii staff as subject matter experts)

What you’ll do

  • In collaboration with the team, you’ll develop a time-series ML approach to optimize emulsion production and reduce emissions
  • Research, critically analyze and implement (build, train, evaluate and maintain) ML solutions
  • Collaborate in cross-functional teams to prototype new concepts, lead and deliver end-to-end systems from design to execution
  • Explore, wrangle, process and model large datasets
  • Formulate and execute a strategic plan for delivering high-quality and continuously integrated machine learning (ML) models
  • Produce high-quality code with excellent reliability and scalability
  • Build, automate and maintain machine learning pipelines
  • Communicate to all stakeholders regarding the approaches and the reasoning

Required Qualifications

  • Graduate degree in Machine Learning or related field or with equivalent experience in Machine Learning
  • 1+ years of experience working with multi-dimensional time-series data
  • Experience with various feature engineering techniques
  • Proficient in Python and related ML libraries (scikit-learn, TensorFlow, Keras, etc.)
  • Experience working with various stages of a machine learning process lifecycle
  • Ability to document and communicate complex technical topics to technical and non-technical stakeholders
  • General understanding of the strengths and weaknesses of a range of ML techniques across different areas in machine learning
  • Must be legally eligible to work in Canada

Preferred Qualifications

  • Experience using machine learning for prediction/classification in geologic domain is an asset
  • Experience working with Databricks and MLFlow
  • Theoretical knowledge and practical experience with advanced statistical and machine learning analysis techniques
  • Publication record in peer-reviewed academic conferences or relevant journals
  • Positive attitude towards learning and understanding a new domain

Attributes and Expectations

  • Critical and independent thought
  • Collegiality and willingness to listen to feedback and support teammates
  • Intellectual curiosity and the desire to learn new things, techniques, and technologies
  • Able to work independently and make informed decisions while collaborating with staff and subject matter experts when appropriate
  • Able to identify gaps in knowledge and triage their own learning appropriately
  • Flexibility and willingness to adapt, including working with disparate data, skill levels, and client needs

About Amii

One of Canada’s three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world’s top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

What you'll love about us

  • A professional yet casual work environment that encourages the growth and development of your skills.
  • A chance to learn from amazing teammates who support one another to succeed.
  • Competitive compensation including paid time off and flexible health benefits.
  • A modern office located in downtown Edmonton, Alberta.

How to Apply

If this sounds like the opportunity you've been waiting for, please don’t wait for the closing date to apply - we’re excited to add a new member to the Amii team for this role, and the posting may come down sooner than the closing date if we find the right candidate!

When sending your application, please send your resume and cover letter indicating why you think you'd be a fit for Amii by December 14 through the Indeed listing. In your cover letter, please include one professional accomplishment you are most proud of and why.

Amii is proud to be an equal opportunity employer. We are committed to creating a diverse, inclusive and excellent workforce.

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