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Position Details: Developer- Python

Location: Remote, Travel
Openings: 1

Description:

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.






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