Team lead ML Engineer

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About the Role

Our Client is expanding its AI & Data division and is looking for an experienced Machine Learning Engineer to design, develop, and deploy advanced ML solutions that power automation and digital transformation initiatives.

This role combines hands-on engineering with technical leadership, focusing on creating scalable, production-ready ML systems that support real-world business processes.

Key Responsibilities

• Design, develop, and integrate machine learning models into production environments.
• Build and maintain data pipelines and model training workflows to ensure reliable and automated processes.
• Develop and enhance the company’s MLOps infrastructure for model lifecycle management, automation, and monitoring.
• Write production-grade Python code and build APIs or services that expose ML models to business applications.
• Continuously monitor, evaluate, and retrain models to maintain accuracy and performance.
• Collaborate with data engineers, annotation teams, software developers, and product managers to align solutions with business objectives.
• Participate in code reviews, documentation, and the definition of engineering best practices.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related discipline.
• 7+  years of hands-on experience developing and deploying machine learning models.
• Proven people management or team leadership experience on a team of 10.
• Strong proficiency in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Solid understanding of MLOps tools and practices (e.g., MLflow, Kubeflow, Airflow).
• Working knowledge of cloud platforms such as AWS, GCP, or Azure.
• Excellent analytical thinking, problem-solving, and communication skills.
• Understanding of RPA,PPA service

• Experience with document understanding, OCR, or NLP models.
• Familiarity with containerization (Docker, Kubernetes) and CI/CD for ML pipelines.
•  Fluent in English, both written and spoken.

Nice to Have

• Exposure to data governance, model monitoring, or AI observability tools.

Why Join Them

• You’ll be part of a growing AI team within a well-established organization that is transforming its services through technology.
• You’ll work on end-to-end ML systems, from data ingestion to deployment, with real business impact across automation and document intelligence domains.
• If you’re passionate about building scalable ML products and want to see your models running in production, this is the right environment for you.