Description

Lead research and development of generative AI models, multimodal systems, and autonomous agentic architectures.

This role is hybrid.

Responsibilities

• Conduct original research on generative AI, focusing on model architecture, training methodologies, and evaluation strategies for NLP and Deep Learning.
• Design and implement multimodal generative models integrating text, images, and other data types; develop and present proofs of concept to stakeholders.
• Develop autonomous AI systems with agentic behavior, enabling independent decision-making in dynamic environments.
• Optimize generative AI algorithms for efficiency and scalability using parallelization, distributed computing, and hardware acceleration techniques.
• Manage data preprocessing, feature engineering, and model validation, ensuring rigorous experimentation and iterative refinement to meet performance benchmarks.

Required Skills

• 8+ years of experience in AI/ML research and development.
• Strong programming skills in Python with frameworks like PyTorch or TensorFlow.
• Deep understanding of Deep Learning architectures including CNNs, RNNs, LSTMs, Transformers, and LLMs (e.g., BERT, GPT).
• Familiarity with AI agent frameworks such as LangGraph, CrewAI, or Autogen for developing, deploying, and evaluating agents.
• Experience testing and deploying open-source LLMs from Hugging Face, Meta-Llama, BLOOM, or Mistral AI.
• Hands-on experience with ML platforms: Vertex AI (GCP), Azure AI Foundry, or AWS SageMaker.
• Proficiency in cloud data analytics services (BigQuery, Synapse) and MLOps/LLMOps for large-scale deployment.

Preferred Skills

• Ability to create scalable technical architectures and perform comparative analysis across hyperscaler tools.
• Strong foundation in data analytics services offered by Google Cloud, AWS, or Azure.

Key Skills

Education

Any Graduate