Machine Learning Engineer

Job Description Location: Hybrid - Toronto | Standard Business Hours What do we bring to the table? - Benefits begin immediately upon hire. Competitive and flexible medical and dental plans-basic and enhanced options to choose from (drug and non-drug fertility coverage, prescription, vision, paramedical, dental and separate category of mental health support). Variety of spending accounts to allocate leftover flex credits. - Free unlimited access to virtual family health care. - Retirement Savings plan: Employee contribution of 3% with optional 1 or 2% and Kraft Heinz required contribution of 5% with 150% match on optional employee contribution. - Business Resource Groups (BRGs). - Award-winning Ownerversity learning & development resource library. - Employee Assistance Program (EAP) for mental health support. - Learn more about life #hereatKraftHeinz on our YouTube channel! Machine Learning Engineer 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 the correct result. 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. Why Should You Join the Team? The Machine Learning Operations (MLOps) is a new team and is instrumental in guiding the Advanced Analytics journey at Kraft Heinz. As a part of this highly energetic team, you will be responsible for creating/maintaining model pipelines and putting models into production. You will also get opportunities to expand your horizons working with the data scientists to develop ML models and the best-in-class architecture using industry best practices. Overall, if you are passionate about applying technology to solve practical business problems, developing intelligent tools, and working with a friendly team to drive business value, this is going to be your dream team to enrich your career. The sky is not the limit in terms of enhancing your knowledge and working on a variety of projects with the Data Science team at Kraft Heinz! What's on the menu? - 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 - Write production-level code - Bring code to production and engage in code reviews - Use of problem-solving, advanced Analytics methodologies (ML/AI) knowledge to derive the architecture of ML models and assist in the development of new models Recipe for Success: Apply Now if this sounds like you! - I have an understanding of the major modeling techniques and how to apply them (Linear and Logistics Regression, Bayesian, Time series, Confidence interval, Deep Learning etc.) - I have experience in role 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 strong experience developing CI/CD pipelines - I am fluent in version control tools and practices (Github, Azure DevOps). - I have project management experience and strong communication skills Please note: This job posting is just a preview of the full scope of the position. A comprehensive job description is shared upon interview. We hope to find you a seat at our table! Location(s): Toronto - Queen's Quay - Headquarters Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes. In order to ensure reasonable accommodation for protected individuals, applicants that require accommodation in the job application process may contact [email protected] for assistance.