Back
Senior, niche LLM/ML lead role at Tier-1 reduces candidate density.
LLM and cloud MLOps skills are transferable across industries but require specific ML experience, so medium sensitivity.
Multiple mandatory requirements including 8+ years, LLM expertise, cloud deployments, and leadership make filters strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design and deployment of scalable AI/ML and LLM-based data processing pipelines using open-source models and frameworks.
Architect and implement backend systems and APIs in Python, ensuring performance, scalability, and reliability across distributed frameworks.
Lead technical teams, mentor engineers, manage escalations, and drive adoption of cloud-native AI/ML infrastructures primarily on AWS with DevOps automation.
8+ years of software development experience, including at least 3 years in senior or lead roles delivering ML/AI solutions in cloud environments.
Strong expertise in LLM prompt engineering, model fine-tuning, and use of AI/ML frameworks like Hugging Face, LangChain, and LangGraph.
Proficient in Python for API/microservice development (FastAPI, Flask, Django) with strong coding and testing practices.
Hands-on experience deploying and scaling ML/AI services on AWS (preferred), Azure, or GCP using containers, serverless technologies, and Infrastructure as Code.
Experienced technical leader with a track record of architecting and delivering production-grade AI/ML solutions at scale in cloud environments.
Deep practical knowledge of end-to-end ML/AI pipeline automation and modern AI/ML frameworks to enable rapid product innovation.
Operates effectively as the cross-team technical escalation point and mentor, balancing architectural vision with delivery and operational excellence.