Enable

About the Company

Enable helps manufacturers, distributors, and retailers turn rebates into a strategic growth engine. Enable's easy-to-use, collaborative, scalable rebate management platform lets you take control of your rebates, showing the influence and impact strategic rebate programs have on your company's growth, returns, and opportunities.

Our goal is to make a rebate management platform that is fully:

• Comprehensive: Effectively manage every deal type while tracking, analyzing and optimizing the entire rebate management process.

• Collaborative: Create, negotiate, and execute deals together, then track progress in real-time in one trusted location to promote better alignment.

• Controlled: Share the data you want to share, both internally and externally, while configuring workflows, approval processes and audit trails to maintain transparency and compliance.

Listed Jobs

Company Name

Enable

Job Title

Associate Machine Learning Engineer

Job Description

**Job Title** Associate Machine Learning Engineer **Role Summary** Junior ML engineer responsible for building and maintaining data pipelines, ensuring data quality, developing synthetic data and automated labeling, and supporting MLOps for model deployment and monitoring. **Expected Outcomes** - Deliver clean, validated datasets and robust validation tools. - Create and test synthetic data to enhance training sets and edge‑case simulation. - Build CI/CD and MLOps workflows that enable seamless model deployment and monitoring on cloud platforms. **Key Responsibilities** - Clean, validate, audit datasets, identify and resolve anomalies, biases, and missing values. - Develop automated validation tools using Python (pandas, Great Expectations). - Design and generate synthetic datasets via GANs, VAEs, or rule‑based simulation; evaluate their impact on model training. - Support automated labeling pipelines (Snorkel, weak supervision, active learning) and collaborate with annotation teams to improve workflows. - Deploy and monitor models in production (Azure) using Docker, Airflow, MLflow; build CI/CD pipelines for model testing and retraining. - Document processes, maintain performance dashboards, and provide cross‑functional communication. **Required Skills** - Python (NumPy, pandas) and SQL fundamentals. - Data preprocessing, validation techniques, and familiarity with synthetic data tools (Synthea, Faker). - MLOps tools experience (Kubeflow, TFX, Docker, Airflow, MLflow). - Cloud platform knowledge (AWS, GCP, Azure). - Strong analytical, problem‑solving, and data integrity focus. - Effective verbal and written communication for cross‑team collaboration. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Data Science, or a related technical field (or equivalent practical experience). - Foundational experience with data pipelines, model development, or ML workflows through coursework or early professional projects.

Toronto, Canada

Hybrid

20-11-2025