Machine Learning Engineering I, Brampton Ontario
What You'll Do:- Develop and implement robust Machine Learning and AI platform solutions, contributing to the full lifecycle from data preparation, experimentation, and model development to deployment, monitoring, and continuous improvement.
- Support the development of scalable AI platform capabilities, including reusable services, tools, APIs, and infrastructure that enable teams to build, deploy, and operate ML and GenAI solutions efficiently.
- Collaborate on the architecture and implementation of MLOps and LLMOps pipelines to automate and streamline model deployment, versioning, evaluation, monitoring, governance, and lifecycle management.
- Contribute to the implementation and optimization of scalable, secure, and reliable ML and AI infrastructure, leveraging Google Cloud Platform, containerized workloads, K8s,and modern cloud-native engineering practices.
- Build and maintain scalable data pipelines and feature engineering workflows that support analytics, reporting, ML models, and GenAI use cases.
- Work closely with cross-functional teams including product, engineering, analytics, data science, platform, and business stakeholders to deliver high-quality data, ML, and AI platform solutions supporting analytics, reporting, automation, and GenAI initiatives.
- Assist in integrating AI capabilities into enterprise applications and platforms, including model APIs, prompt workflows, retrieval-augmented generation patterns, evaluation processes, and responsible AI controls.
- Monitor the performance, reliability, and quality of ML and AI systems, identifying opportunities for continuous optimization, automation, cost efficiency, and improved user experience.
- Stay current with emerging technologies and industry trends in data engineering, ML, MLOps, AI platforms, and GenAI, applying new knowledge to enhance our solutions.
- Participate in project delivery, technical planning, documentation, and operational support to ensure successful execution and adoption of data, ML, and AI platform projects.
What You Bring:- Bachelor's or master's degree in computer science, Data Science, Engineering, or a related field.
- 1-2 years of hands-on experience in Data Science, ML Engineering, Data Engineering, AI Platform Engineering, or a related technical domain.
- Experience designing, implementing, or supporting data platforms, ML systems, or AI solutions on cloud platforms, preferably Google Cloud Platform.
- Strong technical knowledge of data and ML architecture, ML models, ETL/ELT processes, APIs, distributed computing concepts, and cloud-native development.
- Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Experience with MLOps tools and platforms such as MLflow, Kubeflow, Vertex AI, Vertex AI Pipelines, model registries, experiment tracking, and model monitoring.
- Exposure to GenAI or AI platform concepts, such as large language models, prompt engineering, embeddings, vector databases, retrieval-augmented generation, model evaluation, or responsible AI practices.
- Experience designing or contributing to CI/CD pipelines, automated testing, infrastructure-as-code, or deployment workflows.
- Familiarity with containers, APIs, orchestration, and cloud services, such as Docker, Kubernetes, Cloud Run, Cloud Functions, Pub/Sub, BigQuery, or related technologies.
- Excellent communication, problem-solving, and collaboration skills, with the ability to work effectively within a team and partner with technical and non-technical stakeholders.
Nice to Have- Experience with Vertex AI, Gemini, LangChain, MCPs, vector databases, or enterprise GenAI application patterns.
- Familiarity with LLMOps practices, including prompt versioning, model evaluation, guardrails, hallucination mitigation, observability, and feedback loops.
- Experience building or supporting shared platforms, developer tooling, reusable templates, or self-serve capabilities for data science, ML, or AI teams.
- Understanding of responsible AI, data privacy, security, and governance considerations in enterprise AI environments.
What Loblaw Offers YouWe offer flexibility and balance, and an environment that sets you up for success no matter where your workspace is located. Here, you will find a great team to help you achieve your goals as you help us achieve ours! Work in our fast-paced, exciting Technology environment, helping our stores, colleagues, and customers every day.
Loblaw colleagues also enjoy:
- Work Perks Program
- On-site Fitness, Basketball & Volleyball courts, Ice Rink, Dry Cleaning services at 1PCC Office
- Tuition Reimbursement & Online Learning
- Pension & Benefits
- Paid Vacation
If you're up to the challenge, then we would love to hear from you. Apply today, and get the process started.
Hiring Range / Échelle salariale à l'embauche :
$80,000.00 - $110,000.00 / 80.000,00$ - 110.000,00$ (per year / par an)
A candidate's experience and knowledge as well as the geographical region in which the position is located may be factored into the pay a candidate receives for this position. This posting is for an existing vacancy. The Company uses artificial intelligence for the purpose of screening, assessing and/or selecting applicants for this position. / L'expérience et les connaissances d'un candidat ainsi que la région géographique dans laquelle le poste est situé peuvent être prises en compte dans la rémunération qu'un candidat reçoit pour ce poste. Cette offre d'emploi concerne un poste vacant existant. L'entreprise utilise l'intelligence artificielle dans le but de filtrer, d'évaluer et/ou de sélectionner les candidats à ce poste.
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