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Enabling Exceptional Customer Experiences - Unleash AI-Powered, Merchant-Funded Rewards with Pulse iD
Tech Lead – Data, Artificial Intelligence
Location
Sri Lanka
Posted
148 days ago
Salary
0
Seniority
Senior
Job Description
Tech Lead – Data, Artificial Intelligence
Pulse iD
• Design, build, and lead the delivery of production-grade AI systems focused on Data and AI on Customer Segmentation, Hyper-Personalization, and Intelligent Decisioning. • Own end-to-end production-grade AI initiatives—from data and model design to deployment, monitoring, and optimization. • Lead the design, development, and deployment of AI/ML solutions for Agentic AI, Segmentation, Clustering, Hyper-personalization, Recommendation systems, and predictive use cases. • Translate business objectives into scalable AI solutions and technical roadmaps. • Own the full model lifecycle, including experimentation, training, evaluation, deployment, monitoring, and retraining. • Develop and maintain production-grade AI services using Python. • Design and implement API-driven AI systems using FastAPI. • Work with architect(s) to develop scalable, secure, and resilient AI solutions on AWS. • Use AWS SageMaker for model training, pipelines, and deployment. • Use AWS Bedrock for foundation models, GenAI workflows, and prompt-based solutions. • Lead and implement MLOps best practices across the AI lifecycle. • Build CI/CD pipelines for ML workflows. • Manage model versioning, lineage, and reproducibility. • Ensure reliable and scalable model serving in production environments. • Act as the technical owner for AI initiatives, ensuring timely and high-quality delivery. • Mentor AI/ML engineers through code reviews, architecture discussions, and best practices. • Collaborate with Product, Engineering, and Business stakeholders to align AI outcomes with product goals.
Job Requirements
- Strong proficiency in Python for AI/ML and backend development.
- Hands-on experience building APIs using FastAPI.
- Strong experience with AWS SageMaker, including training jobs, pipelines, and endpoints.
- Practical experience with AWS Bedrock and foundation model integration.
- Solid understanding of machine learning techniques for segmentation and personalization.
- Cloud-agnostic AI/ML development experience is considered a strong advantage.
- Hands-on experience with offline models and on-premises LLM deployments will be an added advantage.
- Minimum 3 years of hands-on experience in MLOps.
- Experience with model deployment, monitoring, and lifecycle management in production.
- Strong experience building cloud-native AI systems on AWS/ Google/ on-premise.
- Experience working with data lakes, data pipelines, ETL/ELT processes, and feature engineering workflows (Nice to have).
- Understanding of data warehouses, data lakes, and scalable data architectures (Nice to have).
Benefits
- Enjoy flexibility through a remote-friendly and globally connected work culture.
- Access career growth opportunities in an innovative, high-growth environment.
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