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 platforms
- Hands-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