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Machine Learning Ops Engineer
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WHO WE ARE:Based in Mississauga, Canada, Invafresh is a leading technology company specializing in fresh food retail operations software for supermarket chains around the world. In business since 1988, Invafresh continues to invest heavily in its people and technology. Today, Invafresh is an organization of experienced and retail-savvy technologists equipped with industry specific solutions that supermarket chains leverage to succeed in the field of fresh operations.Our fresh food retail operations solutions are deployed collectively in over 20,000 supermarket stores worldwide, actively supporting the in-store execution of fresh operations. We enable our customers to achieve and maintain a leadership position in their fresh food offering by providing data integrity and decision support tools needed to enhance sales, minimize loss and inventories, and improve overall margins. We help our customers achieve success in the highly competitive grocery market.THE ROLE:We are seeking a talented and experienced Mid-Level ML Ops Engineer to join our dynamic team. In this role, you will be instrumental in operationalizing and scaling our forecasting, optimization, and artificial intelligence solutions. You will build solutions to ensure continuous integration and delivery (CI/CD), maintain model visibility, track performance, ensure data quality, and improve model performance. This role sits at the intersection of data science, data engineering, and IT operations, ensuring seamless integration and optimal performance of our machine learning models in production.Key Responsibilities:Architect and implement end-to-end machine learning solutions, ensuring seamless deployment and management of ML models.Utilize Azure Databricks and related tools for collaborative data processing and analytics, optimizing our big data workflows.Maintain CI/CD pipelines for ML solutions, enhancing our ability to deliver high-quality solutions rapidly.Manage the machine learning lifecycle, leveraging tools like MLflow, ensuring optimal quality and reproducibility.Implement and maintain monitoring systems to track the performance of deployed models in real-time. Collaborate with cross-functional teams, including data scientists, data engineers, and IT operations, to ensure alignment and successful project delivery.Collaborate with Data Scientists and Data Engineers to ensure high standards of data quality and continuous improvement of model performance.Qualifications:Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.3+ years of experience in machine learning, data science, or a related role.Proficiency in Python, PySpark, and SQL.Strong experience with ML libraries such as scikit-learn, TensorFlow, Keras, and PyTorch.Solid understanding of Git for version control and collaboration.Experience deploying Machine Learning solutions in Azure. Effective communication and collaboration skills.Preferred Qualifications:Experience with containerization and orchestration tools like Docker and Kubernetes.Knowledge of big data technologies, including Databricks.Proficiency in DevOps practices and tools like Azure DevOps, Jenkins, and Terraform.Experience with experiment tracking tools such as MLflow.WHY INVAFRESH?Competitive compensation, flex hours and a comprehensive benefits packageWe take great pride in our first-class team and culture. Open-door approach at all levels.Entrepreneurial and rapid growth company.The premium and most progressive product on the market. Focus on continuous innovation.Work hard/Play hard mentality; we thrive on change and continuously strive for excellence.Real-time coaching and feedback, growth opportunities, and a supportive and collaborative team
