AI Engineer (LLM)

TL;DR

AI Engineer (LLM): Building, fine-tuning, deploying, and scaling large language model–based systems with an accent on LLM optimization, backend API development, and MLOps. Focus on taking LLMs from experimentation to production-ready, scalable AI solutions, implementing RAG pipelines, and ensuring efficient model serving and automated evaluation.

Location: Noida, Uttar Pradesh (Hybrid)

Company

hirify.global is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies, delivering digital solutions to accelerate business growth through innovation.

What you will do

• Design and implement traditional ML and LLM-based systems and applications.
• Optimize model inference performance and cost efficiency.
• Fine-tune foundation models for specific use cases and domains.
• Build robust backend infrastructure for AI-powered applications.
• Implement and maintain MLOps pipelines for AI lifecycle management.
• Design and implement comprehensive traditional ML and LLM monitoring and evaluation systems.

Requirements

• 4–8 years of relevant experience in LLMs, Backend Engineering, and MLOps.
• Experience with LLM expertise including parameter-efficient fine-tuning (LoRA, QLoRA), inference optimization (quantization, pruning), prompt engineering (RAG), and model evaluation.
• Proficiency in Python with FastAPI, Flask, or similar frameworks for backend engineering.
• Experience with RESTful APIs, real-time systems, and vector/traditional databases.
• Hands-on experience with cloud platforms like AWS, GCP, or Azure, focusing on ML services.
• Expertise in MLOps, including model serving frameworks (vLLM, SGLang, TensorRT), Docker, Kubernetes, CI/CD, and workflow orchestration tools like Airflow.

Nice to have

• Hands-on experience with LLM Frameworks like Transformers, LangChain, or LlamaIndex.
• Knowledge of LLM-specific monitoring tools and general ML monitoring.
• Experience with distributed training and inference setups.
• Knowledge of model compression techniques (distillation, quantization).
• Experience deploying models handling high-throughput, low-latency requirements.
• Familiarity with recent LLM research and ability to implement novel techniques.

Culture & Benefits

• Competitive salary and strong insurance package.
• Extensive learning and development resources for employee growth.