AI Engineer / GenAI Specialist

• Develop and deploy AI models for Natural Language Processing (NLP), Computer Vision, and Predictive Analytics, enabling businesses to automate decision-making, enhance customer experiences, and drive innovation.
• Design and implement deep learning and machine learning algorithms, leveraging frameworks such as Tensor

  Flow, Py

  Torch, Keras, and Scikit-learn to solve complex data problems.
• Work with Large Language Models (LLMs) and Generative AI, fine-tuning and integrating solutions like GPT, BERT, Llama, and Stable Diffusion for advanced text, image, and speech-based applications.
• Optimize and fine-tune AI models for scalability and efficiency, ensuring low-latency performance in production environments through quantization, model pruning, and distributed computing.
• Develop APIs and integrate AI models into production systems, working with Flask, Fast

  API, or cloud-based AI services (AWS Sage

  Maker, Google Vertex AI, Azure AI) to deliver real-world applications.
• Enhance AI explainability and interpretability, ensuring ethical AI practices by implementing techniques such as SHAP, LIME, and adversarial robustness testing.
• Stay updated on AI advancements, researching and experimenting with new architectures, zero-shot learning, reinforcement learning, and self-supervised models to maintain a cutting-edge AI strategy.
• Ensure data privacy, bias mitigation, and compliance, following best practices in AI governance, responsible AI frameworks, and regulatory standards such as GDPR and HIPAA.

Responsibilities

• Develop and deploy AI models for Natural Language Processing (NLP), Computer Vision, and Predictive Analytics, enabling businesses to automate decision-making, enhance customer experiences, and drive innovation.
• Design and implement deep learning and machine learning algorithms, leveraging frameworks such as Tensor

  Flow, Py

  Torch, Keras, and Scikit-learn to solve complex data problems.
• Work with Large Language Models (LLMs) and Generative AI, fine-tuning and integrating solutions like GPT, BERT, Llama, and Stable Diffusion for advanced text, image, and speech-based applications.
• Optimize and fine-tune AI models for scalability and efficiency, ensuring low-latency performance in production environments through quantization, model pruning, and distributed computing.
• Develop APIs and integrate AI models into production systems, working with Flask, Fast

  API, or cloud-based AI services (AWS Sage

  Maker, Google Vertex AI, Azure AI) to deliver real-world applications.
• Enhance AI explainability and interpretability, ensuring ethical AI practices by implementing techniques such as SHAP, LIME, and adversarial robustness testing.
• Stay updated on AI advancements, researching and experimenting with new architectures, zero-shot learning, reinforcement learning, and self-supervised models to maintain a cutting-edge AI strategy.
• Ensure data privacy, bias mitigation, and compliance, following best practices in AI governance, responsible AI frameworks, and regulatory standards such as GDPR and HIPAA.

Requirements

• Experience with Tensor

  Flow, Py

  Torch, Hugging Face, Open

  AI API.
• Strong programming skills in Python, Scala, or Java.