Machine Learning Engineer Team Lead

SoftwareOne and Crayon have come together to form a global, AI-powered software and cloud solutions provider with a bold vision for the future. With a footprint in over 70 countries and a diverse team of 13,000+ professionals, we offer unparalleled opportunities for talent to grow, make an impact, and shape the future of technology. At the heart of our business is our people. We empower our teams to work across borders, innovate fearlessly, and continuously develop their skills through world-class learning and development programs. Whether you're passionate about cloud, software, data, AI, or building meaningful client relationships, you’ll find a place to thrive here. Join us and be part of a purpose-driven culture where your ideas matter, your growth is supported, and your career can go global.

Passionate about leading highimpact machine learning initiatives and delivering scalable, productionready AI solutions?

Motivated to mentor and grow a team of ML and data engineers while remaining handson with advanced model development and deployment?

Inspired to join a collaborative Data & AI organisation that values innovation, technical excellence, and continuous learning?

As our new Machine Learning Engineer – Team Lead, you will play a pivotal role in leading the design and delivery of machine learning solutions endtoend, while providing technical leadership and mentorship to a small, highperforming engineering team. You will bridge business objectives with advanced ML techniques, guide architectural decisions, and ensure models are productionready, scalable, and continuously improved.

Key responsibilities will include:

• Lead and mentor a team of ML and Data Engineers, providing technical guidance, regular feedback, and supporting professional development.
• Own the endtoend lifecycle of machine learning initiatives, translating business requirements into welldefined ML problem statements, technical solutions, and delivery plans.
• Design, build, train, and evaluate advanced machine learning models, and contribute to architectural decisions for scalable ML pipelines and cloudbased deployments (Azure preferred).
• Partner with MLOps and DevOps teams to implement CI/CD pipelines, model versioning, monitoring, retraining, and production support best practices.
• Collaborate crossfunctionally with Data Engineering, Software Development, Sales & PreSales, and leadership stakeholders, while staying current with emerging ML technologies and driving adoption where valuable.

• Proven experience delivering machine learning solutions into production environments.
• Strong technical expertise in Python and ML frameworks such as TensorFlow, PyTorch, and Scikitlearn.
• Solid understanding of endtoend ML pipelines, data preprocessing, feature engineering, model evaluation, and monitoring.
• Experience working with cloud platforms (Azure preferred), Docker, Kubernetes, and MLOps tooling (e.g., MLflow, Airflow).
• Ability to balance technical depth with leadership responsibilities and commercial awareness and having experience working within agile delivery environments and across multiple stakeholder groups

• Proven experience delivering machine learning solutions into production environments.
• Strong technical expertise in Python and ML frameworks such as TensorFlow, PyTorch, and Scikitlearn.
• Solid understanding of endtoend ML pipelines, data preprocessing, feature engineering, model evaluation, and monitoring.
• Experience working with cloud platforms (Azure preferred), Docker, Kubernetes, and MLOps tooling (e.g., MLflow, Airflow).
• Ability to balance technical depth with leadership responsibilities and commercial awareness and having experience working within agile delivery environments and across multiple stakeholder groups