AI/ ML/ LLM Engineer - Computer Vision

Design, develop, and implement advanced LLM applications using state-of-the-art models and techniques.

Lead research initiatives in Retrieval-Augmented Generation (RAG) systems, improving the accuracy and efficiency of information retrieval and generation.

Conduct experiments on training and fine-tuning large language models for specific domains and tasks.

Collaborate with cross-functional teams to integrate LLM solutions into production systems.

Stay up-to-date with the latest advancements in LLMs, NLP, and deep learning, and apply new techniques to ongoing projects.

Mentor junior team members and contribute to the overall growth of the AI research team.

Publish research findings in top-tier conferences and journals.

Requirements:

2+ years of experience in NLP, deep learning, and building LLM applications.

Strong programming skills in Python, with experience in deep learning frameworks such as PyTorch or TensorFlow.

Extensive experience with transformer-based models (e.g., BERT, GPT, T5) and their applications.

Demonstrated expertise in developing RAG systems and improving their performance.

Proficiency in training and fine-tuning large language models, including techniques like few-shot learning and prompt engineering.

Strong background in NLP techniques, including text preprocessing, tokenization, and embedding methods.

Familiarity with MLOps practices and tools for model versioning, experiment tracking, and deployment.

Excellent problem-solving skills and ability to think creatively about AI solutions.

Strong communication skills and ability to explain complex technical concepts to both technical and non-technical audiences.

IMMEDIATE JOINERS ONLY NEED APPLY.

Preferred Qualifications:

Experience with efficient training techniques for large models, such as distributed training and mixed-precision training.

Knowledge of model compression techniques, including quantization and distillation.

Familiarity with ethical AI practices and bias mitigation in language models.

Experience with multi-modal models combining text with other data types (e.g., images, audio).

Contributions to open-source NLP or LLM projects.

Good to have Publication record in top-tier AI conferences (e.g., NeurIPS, ICML, ACL, EMNLP).

Computer Vision Models [Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformer-based Modelsetc)

Object Detection [ Two-Stage Detectors, One-Stage Detectors]

Training CV Models

Image Processing Techniques

.

If you're passionate about advancing the field of large language models and have a track record of building innovative AI solutions, we'd love to hear from you. Join us in shaping the future of AI in ERP industry