AIML Engineer

Key Skills & Expertise

Generative AI & LLMs : Proficiency in GPT-3, Langchain, and LLMs with experience in prompt engineering, few-shot/zero-shot learning, RLHF, and model optimization.

Machine Learning & NLP : Strong experience in Python with deep learning frameworks like Hugging Face, TensorFlow, Keras, and PyTorch. Solid understanding of embeddings and data modeling.

Databases : Experience with vector databases, RDBMS, MongoDB, NoSQL databases (HBase, Elasticsearch), and data integration from multiple sources.

Software Engineering : Expertise in data structures, algorithms, system architecture, and distributed systems.

Platform & Cloud : Hands-on experience with Kubernetes, Spark ML, Databricks, and developing scalable platforms at scale.

API Development : Proficiency in API design, RESTful services, and data mapping to schemas.

Key Responsibilities
• Design, develop, and implement generative AI models using GPT, VAE, and GANs. Optimize LLM performance through fine-tuning, hyperparameter evaluation, and model interpretability.
• Collaborate with ML and integration teams to integrate AI models into scalable web applications.
• Build and maintain distributed systems with robust system architecture. Integrate data from diverse sources and design efficient APIs for seamless functionality.
• Enhance response quality and performance using RLHF and other advanced techniques.

Educational Qualifications & Requirements

Education : B.Tech / B.E. /M.Tech / M.E.
• Proven track record in building and deploying AI/ML models, particularly LLMs.
• Prior experience developing public cloud services or open-source ML software is a plus.
• Knowledge of big-data tools would be a big plus Self-driven and eager to learn