Machine Learning Engineer

Machine Learning Engineer (P823)

About Us:

As a Machine Learning Engineer at Kenility, you’ll join a tight-knit family of creative developers, engineers, and designers who strive to develop and deliver the highest quality products into the market.

 

Technical Requirements:

  • Bachelor’s degree in Computer Science, Software Engineering, or a related field.
  • Over five years of experience in developing, training, and deploying machine learning models in production environments.
  • At least two years working specifically with Azure Machine Learning, including model training, endpoint management, and pipeline orchestration.
  • Strong background in CI/CD automation and version control using Azure DevOps or GitHub Actions tailored for ML projects.
  • Proficient in Python programming, utilizing libraries such as pandas, scikit-learn, xgboost, and joblib.
  • Advanced SQL skills for data extraction, profiling, and transformation.
  • Skilled in producing clear and auditable technical documentation to ensure long-term sustainability.
  • Effective communicator with business users, BI teams, and data engineering professionals.
  • Experience ensuring model reproducibility, traceability, and versioning in production settings.
  • Familiarity with deep learning frameworks like PyTorch or TensorFlow is a plus.
  • Knowledge of Azure tools including Data Lake, Synapse, Data Factory (ADF), and Key Vault.
  • Exposure to Azure Databricks and notebook development in Spark environments.
  • Experience deploying ML models on Azure Kubernetes Service (AKS).
  • Understanding of ML integration with Power BI or Power Platform.
  • Monitoring experience using Azure Monitor, Log Analytics, or Application Insights.
  • Awareness of fairness and model explainability techniques such as SHAP and LIME.
  • Holding certifications like Azure AI Engineer (AI-102) or Data Scientist (DP-100) is an advantage.
  • Minimum Upper Intermediate English (B2) or Proficient (C1).

 

Tasks and Responsibilities:

  • Build, train, and deploy machine learning models using Azure Machine Learning in production scenarios.
  • Implement and maintain CI/CD pipelines with Azure DevOps to support ML workflows.
  • Collaborate closely with business teams, BI professionals, and data engineers to align technical solutions with business needs.
  • Maintain model performance through monitoring and ensure reproducibility and traceability across the lifecycle.
  • Document technical processes, decision-making, and workflows to support audits and long-term maintenance.

 

Soft Skills:

  • Responsibility
  • Proactivity
  • Flexibility
  • Great communication skills