Machine Learning Engineer Team Lead

SoftwareOne is a global provider of software and cloud solutions. With a presence in over 70 countries and more than 12,000 professionals, we help organizations optimize software investments, modernize applications, and unlock the value of cloud, data, and AI.

Our people are at the core of everything we do. We enable collaboration across borders, continuous learning, and opportunities to grow in a fast-evolving technology landscape. Whether your focus is on technology, customer success, or business operations, your ideas matter, and your contributions make a difference.

Join a global team where you can build your skills, work with leading technologies, and make a real impact for our customers.

Passionate about leading high‑impact machine learning initiatives and delivering scalable, production‑ready AI solutions?

Motivated to mentor and grow a team of ML and data engineers while remaining hands‑on 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 end‑to‑end, while providing technical leadership and mentorship to a small, high‑performing engineering team. You will bridge business objectives with advanced ML techniques, guide architectural decisions, and ensure models are production‑ready, 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 end‑to‑end lifecycle of machine learning initiatives, translating business requirements into well‑defined 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 cloud‑based deployments (Azure preferred).
• Partner with MLOps and DevOps teams to implement CI/CD pipelines, model versioning, monitoring, retraining, and production support best practices.
• Collaborate cross‑functionally with Data Engineering, Software Development, Sales & Pre‑Sales, 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 Scikit‑learn.
• Solid understanding of end‑to‑end 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

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