Senior Data Scientist (ML/AI and GenAI) Easygenerator

GenAI Development & Architecture

• Design and build end-to-end Generative AI applications, including RAG pipelines, LLM orchestration, and semantic search solutions

• Collaborate with Product Managers and Engineering Leads to identify high-impact AI opportunities and translate them into scalable architectures

• Apply best practices for distributed ML systems to ensure modularity, maintainability, and scalability

• Optimize AI systems for latency, cost-efficiency, and data privacy

• Establish and promote architectural standards for AI/ML services

MLOps & Production Excellence

• Own the full lifecycle of ML models, from experimentation to production deployment

• Productionize models as scalable microservices using FastAPI, Docker, and Kubernetes (AKS)

• Implement and promote MLOps best practices, including CI/CD, monitoring, and data validation

• Ensure systems are observable, reliable, and aligned with engineering and security standards

• Translate complex AI concepts into practical, implementable solutions for engineering teams

Collaboration & Engineering Culture

• Work closely with Engineering Managers, Data Scientists, and Product teams to deliver impactful AI-driven features

• Mentor and coach team members on software engineering best practices (OOP, testing, system design)

• Establish technical guardrails and reference architectures for AI development

• Foster a culture of experimentation, knowledge sharing, and evidence-based decision-making

• Contribute to improving documentation and AI/ML knowledge across the organization

Hands-On Development & Innovation

• Build proof-of-concepts and run technical experiments to validate new approaches

• Contribute to design reviews and key architectural decisions involving AI/ML

• Stay close to delivery teams to ensure solutions are practical and production-ready

• Support the development of AI-powered features such as search, recommendations, and document intelligence