Artificial Intelligence (Generative AI) Engineer
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Job Description
About the Company:
Beehive AI offers a generative AI platform specifically built for analyzing an organization’s unique qualitative data. The platform uses self-learning language models validated by human experts and incorporates built-in statistical analysis. This allows research and insights leaders to quickly, accurately, and securely analyze qualitative data, combining it with quantitative data for more robust customer insights. Beehive AI integrates with any existing insights program within an organization, eliminating data silos and promoting a consistent analytical approach. Unlike traditional ML/NLP tools (requiring manual setup and maintenance) or generic LLM-based generative AI solutions (posing data security risks), Beehive AI utilizes generative AI and LLMs tailored to each organization. This ensures safe and scalable qualitative data analysis, enabling the combination with quantitative data to generate precise, real-time business and customer insights.
About the Position: Artificial Intelligence (Generative AI) Engineer
As a Generative AI Engineer at Beehive AI, you will be responsible for the design, development, experimentation, and maintenance of various components within the Beehive AI algorithms and LLMs. This role demands independent work across the entire development lifecycle, from researching and experimenting with generative AI solutions to their final implementation and deployment into a production environment.
Responsibilities:
• Researching and experimenting with generative AI solutions.
• Designing, developing, and implementing AI algorithms and LLMs.
• Optimizing model training and addressing complex challenges in model performance.
• Collaborating effectively with cross-functional teams, communicating technical concepts clearly.
• Staying current with the latest trends and advancements in AI and machine learning.
• Implementing and productionalizing developed AI solutions.
Requirements:
• Advanced Degree: PhD in Computer Science, AI, Linguistics, Applied Physics, or a related field with a focus on AI and natural language processing.
• LLM and PyTorch Experience: Extensive experience with large language models and demonstrable proficiency in PyTorch.
• Analytical and Problem-Solving Skills: Proven ability to tackle complex challenges related to model training and optimization.
• Communication and Collaboration Skills: Excellent communication skills for conveying technical information and working effectively within a team environment.
• Innovation and Continuous Learning: A passion for staying abreast of the latest AI and machine learning trends.
• Proficiency in Python: Strong programming skills in Python are essential.
