This role is for one of the Weekday's clients
Salary range: Rs 1800000 - Rs 2000000 (ie INR 18-20 LPA)

Min Experience: 1 years

Location: Bangalore

JobType: full-time

We are looking for a highly motivated AI Engineer with expertise in Large Language Models (LLMs) and Machine Learning (ML) to join our team. In this role, you will be responsible for designing, developing, and optimizing AI-driven applications using the latest advancements in natural language processing (NLP) and machine learning. You will work closely with cross-functional teams to build scalable AI models, fine-tune LLMs, and integrate AI capabilities into real-world applications.

Requirements

Key Responsibilities:

• LLM Development & Fine-Tuning: Work with state-of-the-art Large Language Models (LLMs) such as GPT, LLaMA, or custom transformer-based architectures. Fine-tune models for specific business use cases.
• Machine Learning Model Development: Design, train, and deploy ML models to solve real-world problems, focusing on NLP, predictive analytics, and recommendation systems.
• Data Processing & Engineering: Preprocess and clean large datasets to improve model accuracy. Utilize structured and unstructured data for training robust AI solutions.
• Model Optimization & Performance Tuning: Optimize AI/ML models for scalability, efficiency, and accuracy using quantization, pruning, and distillation techniques.
• AI Integration & Deployment: Work on deploying AI models in cloud environments (AWS, GCP, or Azure), leveraging frameworks like TensorFlow, PyTorch, or Hugging Face.
• Research & Innovation: Stay updated with the latest AI research, contribute to internal AI initiatives, and experiment with new techniques to enhance model performance.
• Collaboration & Problem-Solving: Work with data scientists, software engineers, and product managers to integrate AI-driven features into products.

Skills & Qualifications:

• 1+ years of experience in AI/ML, preferably with a focus on LLMs and NLP.
• Strong proficiency in Python, along with ML libraries like TensorFlow, PyTorch, Scikit-learn, and Hugging Face.
• Hands-on experience in fine-tuning and training LLMs for specific applications.
• Proficiency in ML model training, validation, and evaluation techniques.
• Experience working with data processing libraries such as Pandas and NumPy.
• Familiarity with vector databases (FAISS, Pinecone, or ChromaDB) for efficient search and retrieval in LLM applications.
• Understanding of cloud environments (AWS, GCP, or Azure) and deploying AI models via APIs or microservices.
• Strong problem-solving skills and the ability to work in a fast-paced environment.
• Good communication skills to work effectively in cross-functional teams.

Preferred Qualifications:

• Experience with transformer-based architectures (BERT, GPT, LLaMA, etc.).
• Familiarity with Reinforcement Learning with Human Feedback (RLHF).
• Knowledge of MLOps and model monitoring techniques.
• Understanding of prompt engineering and AI explainability techniques.