Role Descriptions: Technical Leadership Set engineering standards| conduct code reviews| and mentor a team of AI/ML engineers across the full development lifecycle
Model Development Design| build| and optimize machine learning and deep learning models for production use cases including NLP| computer vision| and predictive analytics
Architecture & Infrastructure Define scalable AI/ML system architecture; oversee data pipelines| model training| and deployment infrastructure on cloud platforms (Azure| AWS| GCP)MLOps & Deployment
Establish and maintain CI/CD pipelines| model versioning| monitoring| and retraining workflows to ensure reliability in production
Stakeholder Collaboration Partner with product managers| data scientists| and business teams to translate requirements into technical solutions with measurable outcomes
Evaluation & Governance Define model evaluation frameworks; ensure solutions meet performance| fairness| safety| and compliance standardsInnovation Stay current on emerging AI trends and frameworks; identify opportunities to adopt new tools and techniques that advance team capabilities
Preferred Qualifications
Strong proficiency in Python and ML frameworks (PyTorch| TensorFlow| scikit-learn)Experience with LLMs| prompt engineering| and generative AI platformsHands-on knowledge of cloud-based AI/ML services (Azure ML| AWS SageMaker| Vertex AI)Familiarity with vector databases| RAG pipelines| and API development
Prior experience leading engineering teams in an Agile/Scrum environment
Essential Skills: Lead the end-to-end design| development| and deployment of AI/ML solutions| driving technical strategy and guiding engineering teams to deliver scalable| production-grade AI systems aligned to business objectives.
Desirable Skills:
Keyword:
Skills: Digital : Artificial Intelligence(AI)
Experience Required: 4-6
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