Back
Strong brand, mid-level LLM role in a metro with broad skillset attracts high competition.
LLM, MLOps, and microservices skills are broadly transferable across industries.
Many mandatory technical requirements and explicit 5+ years experience enforce strict shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop, maintain, and optimize microservice architecture and APIs for AI/ML deployment in customer experience projects.
Design and implement scalable data pipelines and LLM inference architectures including GPU memory optimization and model quantization.
Collaborate with cross-functional teams to integrate, fine-tune, and deploy LLM and AI models with CI/CD pipelines and container orchestration (Kubernetes).
5+ years of relevant work experience in AI/ML engineering or related fields.
Bachelor of Engineering degree required; MBA also preferred but not explicitly mandatory.
Advanced proficiency in Python and experience with LLM frameworks (Hugging Face, LangChain), Spark, Git, MLflow, Kubernetes, Terraform/CloudFormation, and cloud platforms (AWS, GCP, or Azure).
Experience with microservices architecture, model deployment, A/B testing, and LLM optimization (quantization, knowledge distillation).
Experienced AI/ML engineer with deep expertise in large language models and scalable microservices for enterprise AI solutions.
Proficient in building robust MLOps pipelines combining software engineering, infrastructure as code, and container orchestration for production deployments.
Capable of translating business/customer needs into advanced NLP/ML solutions, managing experimentation, performance tuning, and collaborating across data science and product teams.