AI Specialist - LLM/Generative AI

Job Description :

We are looking for a talented AI Specialist with expertise in Large Language Models (LLMs) to join our dynamic AI team. In this role, you will be responsible for training, fine-tuning, and optimizing cutting-edge models like LLaMA and Mistral to meet company-specific use cases and enhance our AI-driven solutions. As part of the AI team, you will also collaborate closely with cross-functional teams to integrate these models into production systems and develop data pipelines for scalable AI applications. This role is an excellent opportunity for someone who is passionate about AI advancements and wants to work with the latest techniques in Generative AI (GenAI) and LLM technologies.

Key Responsibilities :

- Train and fine-tune Large Language Models (LLMs) such as LLaMA, Mistral, and other state-of-the-art models for specific business use cases.

- Customize models for optimal performance in various production environments and ensure they meet company-specific requirements.

- Optimize LLM performance by experimenting with techniques like LoRA, QLoRA, RAG, and PEFT to improve model efficiency and reduce resource usage.

- Implement model pruning, quantization, and other techniques for faster inference and lower computational overhead.

- Collaborate with cross-functional teams (engineering, product, and data science) to ensure seamless integration of models into production systems.

- Work closely with data engineers to design, implement, and optimize data pipelines that support large-scale model training and deployment.

- Stay abreast of the latest developments and advancements in Generative AI and LLM techniques, including emerging methods for fine-tuning, model evaluation, and deployment.

- Experiment with new ideas, frameworks, and algorithms to improve the capabilities and performance of LLMs within the organization.

- Perform model evaluation, error analysis, and performance testing to ensure high-quality model outputs.

- Monitor models in production to track performance, gather feedback, and continuously improve model accuracy and usability.

- Document model training processes, configurations, and optimization strategies.

- Provide regular reports and presentations on model performance, results, and next steps to internal stakeholders.

Required Skills & Qualifications :

Experience :

- 3-5 years of hands-on experience working with Large Language Models (LLMs) such as LLaMA, GPT, Mistral, or other similar models.

- Proven experience in training, fine-tuning, and deploying LLMs for real-world use cases.

Technical Expertise :

- Strong proficiency in LoRA, QLoRA, RAG, PEFT, and other techniques for fine-tuning and optimizing LLMs.

- Extensive experience with GPU-based training, distributed computing frameworks (e.g., PyTorch, TensorFlow, DeepSpeed), and cloud platforms like AWS or Azure for training large-scale models.

- Knowledge of model optimization techniques such as pruning, quantization, and low-latency inference for efficient deployment.

Skills & Tools :

- Hands-on experience with LLM architectures and generative AI techniques.

- Proficiency in Python, PyTorch, TensorFlow, or similar AI frameworks for model training and evaluation.

- Experience working with NLP (Natural Language Processing) models, transformer-based architectures, and large-scale AI workloads.

- Experience in building and optimizing data pipelines to handle large-scale datasets for model training.

- Familiarity with ETL processes, data wrangling, and integrating data sources for training and model evaluation.

- Strong analytical and problem-solving skills, with a deep understanding of model evaluation and optimization.