Position Details: Developer- Python

Generative AI (GenAI) Associate

We are seeking a highly skilled and experienced Generative AI (GenAI) Associate to join our team. The ideal candidate will have a strong background in AI, machine learning, and deep learning, with hands-on expertise in developing, deploying, and optimizing generative AI models. The role involves working on cutting-edge AI solutions, collaborating with cross-functional teams, and driving innovation in AI-driven applications.

Key Responsibilities:

• Design, develop, and deploy Generative AI models using state-of-the-art machine learning techniques.
• Work with Large Language Models (LLMs), Diffusion Models, and other generative frameworks to build innovative AI applications.
• Optimize and fine-tune AI models for performance, scalability, and efficiency.
• Conduct research and stay updated with the latest advancements in AI and machine learning.
• Collaborate with data scientists, engineers, and product teams to integrate AI models into production environments.
• Develop robust pipelines for data preprocessing, model training, evaluation, and deployment.
• Ensure ethical AI practices, model interpretability, and bias mitigation in AI systems.
• Document research findings, methodologies, and best practices.
• Provide mentorship and technical guidance to junior team members.

Qualifications:

• Bachelor, Master's or PhD in Computer Science, AI, Machine Learning, or a related field.
• 5+ years of experience in AI/ML, with a focus on Generative AI.
• Strong proficiency in Python and frameworks like TensorFlow, PyTorch, or JAX.
• Experience with LLMs (GPT, BERT, LLaMA, etc.), GANs, VAEs, or Diffusion Models.
• Deep understanding of NLP, computer vision, and reinforcement learning techniques.
• Proficiency in cloud platforms (AWS, GCP, Azure) and AI model deployment.
• Experience with MLOps, CI/CD pipelines, and model monitoring.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.

Preferred Qualifications:

• Experience with prompt engineering and fine-tuning foundation models.
• Familiarity with vector databases, retrieval-augmented generation (RAG), and knowledge graphs.
• Prior experience in AI ethics, fairness, and responsible AI development.
• Contributions to open-source AI/ML projects or research publications in AI conferences.