Machine Learning Engineer Lead

Kraft Heinz Company
Old Toronto
CAD 100,000 - 125,000
Job description

Machine Learning Engineer Lead

Here at Kraft Heinz, we grow our people to grow our business, because we believe that great people make great companies. When you join our table, you can expect access to an array of holistic wellness benefits and perks, including medical, dental and vision coverage, 7% 401(k) matching, Business Resource Groups (BRGs) to help foster diversity, inclusion, and belonging for all employees, an industry-leading total rewards package that emphasizes a high discretionary bonus.

Machine Learning Engineer Group Lead at a glance

The Machine Learning Engineering role is the backbone for the models that drive advanced analytics insights. The role will be responsible for ensuring that the Machine Learning models get the right data at the right time to deliver correct results. This role works closely with the Data Scientist, Cloud and Data Engineering organization for new solution development and operations. This role helps to maximize the ROI on data and technology by enabling ML Models to scale, maintaining models, and assisting in the development of ML models.

What's on the menu?

  • Lead, manage and develop the ML Engineering group in the Toronto office.
  • Responsible for the internal and external labor applied to ML Engineering projects.
  • Manage the ML engineering budget and estimation process.
  • Implement machine learning algorithms and customized libraries.
  • Assist Data Science team with development of complex tools, models or database builds.
  • Collaborate with data engineers and data scientists to develop data and model pipelines.
  • Improve existing Machine Learning models.

Recipe for Success: Apply now if this sounds like you!

  • I have an understanding of the major modelling techniques and how to apply them (Linear and Logistics Regression, Bayesian, Time series, Confidence interval, Deep Learning, etc.).
  • I have experience in managing technical teams delivering and supporting analytical capabilities.
  • I have experience supporting ML models in a production cloud environment (Azure experience preferred).
  • I have “hands-on” experience with analytical tools (preferably AzureML, Vertex, SageMaker, Snowflake, DataBricks, Tableau, Alteryx, SQL, Python, and/or R).
  • I have working knowledge on LLM operations (including fine tuning and grounding techniques) and prompt engineering best practices.
  • I have strong experience developing CI/CD pipelines.
  • I am fluent in version control tools and practices (Github, Azure DevOps).

Please note: This job posting is just a preview of the full scope of the position. A comprehensive job description is shared upon interview.

Location(s)

Toronto - Queen's Quay - Headquarters

Kraft Heinz is an Equal Opportunity Employer

In order to ensure reasonable accommodation for protected individuals, applicants that require accommodation in the job application process may contact NATAI@kraftheinz.com for assistance.

ABOUT US

Kraft Heinz is a global food company with a delicious heritage. With iconic and emerging food and beverage brands around the world, we deliver the best taste, fun and quality to every meal table we touch. We’re on a mission to disrupt not only our own business, but the global food industry.

WHY US

We grow our people to grow our business. We champion great people who bring ambition, curiosity, and high performance to the table as the guardians of our beloved and nostalgic brands.

INCLUSION MATTERS TO US

Everyone is welcome at our table. In fact, we thrive on learning and growing from our diverse backgrounds and perspectives.

We’re committed to:

  • Hiring and growing talent from diverse backgrounds and perspectives.
  • Growing our Business Resource Groups — vibrant, celebrated communities that enhance our business through thought leadership employee engagement and professional development opportunities.
  • Providing our managers and leaders high quality learning experiences to explore how to foster inclusion and belonging.
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