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About the Opportunity
Our client is looking for a Senior ML/AI Engineer to strengthen their data platform by integrating advanced AI capabilities. The role focuses on building scalable, production-ready machine learning solutions while balancing technical excellence with business value and cost efficiency.
Role Overview
The selected candidate will take ownership of end-to-end machine learning workflows, from data processing and feature engineering to model deployment and monitoring. This position requires a strong understanding of the full ML lifecycle along with hands-on experience in cloud-based AI ecosystems.
Key Responsibilities
- Design, develop, and maintain end-to-end machine learning solutions across the full lifecycle
- Transform raw data into meaningful features and deploy scalable models into production environments
- Monitor, evaluate, and continuously improve model performance and reliability
- Collaborate with cross-functional teams to align AI solutions with business objectives
- Optimize development, deployment, and operational costs while ensuring maximum value delivery
- Implement robust engineering practices including version control, testing, and CI/CD pipelines
- Contribute to platform enhancements within Databricks and Azure environments
Required Experience & Qualifications
- Minimum 5+ years of experience in developing and maintaining production-grade ML/AI solutions
- Proven expertise across the complete ML pipeline (data → features → modeling → deployment → monitoring)
- Strong programming skills in Python
- Hands-on experience with Azure AI ecosystem (Azure AI Services, Microsoft Foundry, etc.)
- Experience working with Databricks and cloud-based data platforms
- Proficiency in ML frameworks such as TensorFlow, PyTorch, MLlib, and Scikit-learn
- Practical experience with MLOps tools (preferably MLflow)
- Strong domain expertise in at least one area: NLP, Computer Vision, Time Series, or Anomaly Detection
- Familiarity with software engineering best practices (Git, CI/CD, testing frameworks)
Preferred Skills
- Experience with Retrieval-Augmented Generation (RAG) systems
- Exposure to agent-based systems and Robotic Process Automation (RPA)
- Knowledge of PySpark / Apache Spark
- Experience working with event-driven architectures or streaming data systems
- Prior experience mentoring or guiding junior ML/Data Engineers
Education
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field
Language Requirements
- English: Mandatory (Professional proficiency)
Work Model (Job Mode)
- Hybrid (up to 25% remote work permitted)
- On-site presence required based on client needs
Application Method: Interested candidates can apply by sending their profile to [email protected]