Description

You will design and implement generative AI models and large language models to create high-quality synthetic data and outputs. You own the end-to-end lifecycle from preprocessing large datasets to deploying scalable production systems.

Responsibilities

• Design and implement generative AI models including GANs, VAEs, transformers, and LLMs such as GPT, BERT, and LLAMA.
• Preprocess and analyze large datasets to train and validate AI and LLM models.
• Collaborate with machine learning, data, and software engineers to integrate models into production systems for scalability and performance.
• Analyze statistics, data, and algorithms to ensure projection accuracy and provide strategy recommendations.
• Maintain thorough documentation of all models, experiments, and methodologies.

Required Skills

• 5+ years of experience developing and deploying machine learning models in real-world applications.
• Proficiency in Python, Java, or C++.
• Hands-on experience with GANs, VAEs, transformers, and LLMs (GPT, BERT, LLAMA).
• Experience with TensorFlow, PyTorch, Keras, or Apache MXNet.
• Strong understanding of machine learning algorithms, deep learning architectures, and optimization techniques.
• Familiarity with NLP libraries including NLTK, spaCy, or Transformers.
• Experience with computer vision using OpenCV, TensorFlow Object Detection API, or PyTorch Vision.
• Familiarity with cloud platforms such as AWS, GCP, or Azure.

Preferred Skills

• Experience with Google Cloud Platform (GCP).

Key Skills

Education

Any Graduate