REQUIREMENTS:

• Bachelor’s Degree in Computer Science, Engineering, Data Science, or any other relevant subject.
• Minimum 2 years of experience in Data Science and Machine Learning.
• Deploying LLMs, AI Agents and AI Solutions, integrate and deploy open source AI models and solutions from Huggingface repository.
• In-depth knowledge of machine learning, deep learning, and generative AI techniques.
• Proficiency in programming languages such as Python, R, and frameworks like TensorFlow, PyTorch, Flask, Langchain, Llamaindex, CrewAI and Autogen.
• Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models.
• Familiarity with computer vision techniques for image recognition, object detection, or image generation.
• Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment.
• Expertise in data engineering, including data curation, cleaning, and preprocessing.
• Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems.
• Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.Track record of driving innovation and staying updated with the latest AI research and advancements.
• 
  TOPPAN Ecquaria is an equal opportunity employer and values diversity within our company. We welcome all interested candidates to apply for this position, however, we regret to inform that only shortlisted candidates will be contacted by us for an interview.
  Find us at www.topppanecquaria.com or www.linkedin.com/company/toppan-ecquaria
  For more career opportunities, please visit our career site at:- https://toppanecquaria.com/careers/job-openings?utmsource=Jobstreet&utmmedium=Page&utm_campaign=2020
  (Please copy & paste the above link onto your browser

• Contribute to the design and implementation of AI solutions.
• Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
• Collaborate with stakeholders to identify business opportunities and define AI project goals.
• Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
• Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
• Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
• Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
• Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs.
• Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
• Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.
• Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.
• Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.