What are the responsibilities and job description for the Data Scientist position at Infinity Tech Group Inc?
Job Details
Job Description:
We seek a skilled and forward-thinking Data Scientist with Generative AI experience in large language models (LLMs) such as ChatGPT, LLaMA, DeepSeek, and Vertex AI. The ideal candidate will have a solid understanding of prompt engineering, fine-tuning, embeddings, and model deployment and expertise in leveraging cloud platforms (AWS, Google Cloud Platform, or Azure) to scale AI solutions.
Must skills:
AI(Artificial Intelligence )
ML(Machine Learning)
NLP(Natural Language Processing)
LLMs (Large language models)
Chatbot/ Python, Generative AI, MLOps, sentiment analysis, and text generation techniques
Any cloud (AWS/ Azure/ Google Cloud Platform)
Key Responsibilities:
Designed and architected a scalable, secure, and efficient internal assistant solution using cutting-edge AI and natural language processing technologies
Develop proof-of-concept and prototypes to validate architectural decisions
Lead the integration of the chatbot with internal systems, databases, and APIs
Collaborate with cross-functional teams to gather requirements and ensure alignment with business objectives
Implement best practices for AI model deployment, monitoring, and continuous improvement
Provided technical leadership and mentorship to the development team
Stay up-to-date with the latest advancements in AI, GenAI, and LLMs, incorporating innovative features into the chatbot architecture
Required Qualifications:
10 years of experience in software development, with a focus on AI and machine learning
Proven experience architecting and implementing internal-facing AI chatbot solutions similar to Glean or Rogo
Strong hands-on experience with Python, LLMs, and Generative AI technologies
Deep understanding of natural language processing, sentiment analysis, and text generation techniques
Expertise in cloud platforms (AWS, Azure, or Google Cloud Platform) for AI model deployment and scaling
Experience with MLOps practices and tools for model lifecycle management
Strong problem-solving skills and ability to translate complex business requirements into technical solutions
Excellent communication skills to explain technical concepts to both technical and non-technical stakeholders.
