AI Engineering Manager

About the Client:

Customer is the country’s leading mobile operator company that offers innovative solutions, a unique and personalized approach and high-quality services.

Key Responsibilities:

• Lead, mentor and inspire a team of Data Scientists and MLOps Engineers to develop AI/ML-driven solutions across customer analytics, revenue optimization, and operational efficiency.

• Drive the adoption of cutting-edge AI/ML techniques, including deep learning transformers and Generative AI for telecom-specific use cases.

• Oversee the full AI/ML lifecycle, from experimentation and model development to deployment and monitoring in production.

• Champion the implementation of MLOps best practices, ensuring robust CI/CD framework, experimentation tracking, model monitoring, and automated retraining strategies.

• Support the adoption and governance of enterprise AI/ML platforms such as AWS SageMaker, Dataiku, IBM Watson AI or similar platforms to streamline development and deployment workflows.

• Drive research and implementation of Parameter-Efficient Fine-Tuning (PEFT) methods and prompt engineering strategies for optimizing GenAI models.

• Collaborate closely with BI and Data Engineering to ensure seamless integration of AI/ML solutions into enterprise data and analytics ecosystems.

Required experience:

• Proven experience leading Data Science and MLOps teams.

• Strong background in machine learning, deep learning, NLP and GenAI (LLM/SLM).

• Hands-on experience with modern AI/ML platforms such as AWS SageMaker, IBM Watson AI, Dataiku or similar.

• Expertise in MLOps, CI/CD pipelines, MLflow/Kubeflow and Orchestration frameworks.

• Experience with TensorFlow/PyTorch, Scikit-learn, Keras.

• Experience with vector databases and retrieval-augmented generation (RAG) e2e implementations.

• Experience with cloud environments (AWS is highly preferable) and hybrid AI/ML deployments is an asset.

• Work experience with big data processing frameworks such as Spark or Hadoop is an advantage.

• Telecom industry experience is a strong plus.

• Fluency in English

Skills and Competencies:

• Passionate about AI/ML, MLOps/LLMOps, and staying ahead of industry trends.

• Strong problem-solving and analytical skills with the ability to drive business impact through AI.

• Excellent communication and stakeholder management skills, bridging the gap between technical and business teams.

• Strategic thinker with a hands-on approach to execution.