Tipstat | AI Engineer

3 days ago

bangalore, India Tipstat Full time

We're seeking an experienced AI Engineer with deep expertise in open-source Large Language Models (LLMs) to join our team. In this role, you'll be responsible for training, fine-tuning, and deploying state-of-the-art language models while pushing the boundaries of what's possible with open-source AI.


Key Responsibilities

- Lead the implementation and optimization of open-source LLMs including LLAMA, Mistral, and DeepSeek models

- Design and execute model training pipelines, including pre-training and fine-tuning strategies

- Develop and implement efficient deployment strategies for LLMs across various infrastructure environments

- Optimize model performance, focusing on inference speed, memory usage, and computational efficiency

- Create and maintain MLOps pipelines for continuous model improvement and deployment

- Collaborate with cross-functional teams to integrate LLM capabilities into production applications

- Research and evaluate emerging open-source models and techniques to keep our technology stack current


Required Qualifications

- Demonstrated experience training and fine-tuning open-source LLMs (LLAMA, Mistral, DeepSeek)

- Strong proficiency in PyTorch and transformers libraries

- Expertise in distributed training techniques and optimization methods

- Experience with quantization, pruning, and other model optimization techniques

- Strong understanding of MLOps practices and deployment frameworks

- Proficiency in Python and software development best practices


Technical Skills

- Deep understanding of transformer architecture and attention mechanisms

- Experience with training frameworks: DeepSpeed, Accelerate, FSDP

- Familiarity with quantization techniques: QLoRA, GPTQ, GGUF

- Knowledge of deployment solutions: vLLM, text-generation-inference

- Experience with MLOps tools: Weight & Biases, MLflow, DVC

- Proficiency in containerization and orchestration: Docker, Kubernetes

- Understanding of prompt engineering and instruction tuning


Preferred Qualifications

- Experience contributing to open-source LLM projects

- Publications in NLP, LLM, or related fields

- Experience with multi-modal models

- Knowledge of model evaluation frameworks and metrics

- Familiarity with RAG (Retrieval-Augmented Generation) implementations

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