Ml Engineer Jobs

About The Position

Requirements

• Excellent knowledge of ML algorithms (e.g., Linear Regression, Logistic Regression, Clustering/Segmentation, Decision Tree, Random Forest, GBM, DNN, Naive Bayes, Support Vector Machine, etc.)
• Data-oriented programming languages
• Visualization software
• Data mining
• Data modeling
• Natural language processing
• Machine learning
• Azure Machine Learning and associated SDKs
• Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and Azure Data Lake Storage (ADLS)
• Azure Kubernetes Service (AKS), Azure Container Instances, or Azure Functions
• Azure DevOps or GitHub Actions
• Experience with large‑scale structured and unstructured datasets

Nice To Haves

• Experience with reinforcement learning paradigms
• Experience with computer vision
• Experience with recommendation systems

Responsibilities

• Responsible for developing and implementing AI-assisted marketing analytics solutions that address customer needs using data science and machine learning.
• Work closely with multi-functional teams to deliver innovative solutions that drive business growth and improve customer engagement.
• Design, implement, and optimize machine learning models across supervised, unsupervised, and reinforcement learning paradigms.
• Develop solutions involving Natural Language Processing (NLP), computer vision, recommendation systems, and predictive analytics.
• Perform feature engineering, data preprocessing, model selection, and hyperparameter tuning.
• Experiment with and evaluate novel algorithms and advanced ML techniques to solve complex business problems.
• Build, train, and deploy models using Azure Machine Learning and associated SDKs.
• Design and maintain scalable data and ML pipelines using Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and Azure Data Lake Storage (ADLS).
• Deploy and operationalize models using Azure Kubernetes Service (AKS), Azure Container Instances, or Azure Functions.
• Implement CI/CD and MLOps best practices using Azure DevOps or GitHub Actions for model versioning, testing, and deployment.
• Monitor model performance, data drift, and model health; retrain models as required to ensure continued accuracy and reliability.
• Optimize inference performance, cost, and resource utilization in Azure environments.
• Collaborate closely with Data Engineers to ingest, transform, and manage large‑scale structured and unstructured datasets.
• Ensure high standards of data quality, consistency, security, and governance in compliance with enterprise and regulatory requirements.
• Work with software engineers, data scientists, and product managers to seamlessly integrate ML solutions into business applications and platforms.
• Stay current with emerging trends in machine learning, AI, and Azure cloud technologies.
• Evaluate new tools, frameworks, and libraries to continuously enhance solution quality and performance.
• Mentor junior engineers and data scientists, promoting best practices in ML development, cloud architecture, and MLOps.

Benefits

• Medical, dental, and vision coverage
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Vacation: 12-25 days, depending on grade
• Company paid holidays
• Personal Days
• Sick Leave