About the role
Responsibilities:
- Lead end-to-end AI/ML solution development from problem definition to deployment and monitoring.
- Design, build, and optimize machine learning and deep learning models for business use cases.
- Develop scalable data pipelines for feature engineering, model training, evaluation, and inference.
- Collaborate with engineering, product, and business teams to deliver production-grade AI solutions.
- Drive MLOps best practices, including CI/CD, monitoring, retraining, and governance.
- Mentor data scientists and provide technical leadership across projects.
- Present technical recommendations and solution architecture to senior stakeholders.
Requirements:
- Bachelor's, master's, or PhD in computer science, AI, data science, statistics, mathematics, or a related field.
- 8+ years of experience in data science, machine learning, or artificial intelligence.
- Strong expertise in Python and SQL.
- Hands-on experience with PyTorch, TensorFlow, Scikit-learn, MLflow, Docker, Kubernetes, and cloud platforms (AWS/Azure/GCP).
- Strong understanding of machine learning algorithms, deep learning, feature engineering, model deployment, and MLOps.
- Proven ability to lead complex technical initiatives and mentor teams.
Preferred Qualifications:
- Experience with GenAI/LLMs, NLP, forecasting, recommendation systems, or computer vision.
- Experience building enterprise-scale AI platforms and production ML systems. Telecom domain experience is an advantage.