POSITION & COMPANY OVERVIEW

Resupply is looking for an innovative and driven AI Engineer to join us on our journey to reinvent and forever change the supply-chain of charitable contributions within the U.S. We are seeking someone who will be passionate about our mission and partnerships as we turn household goods into emergency relief for those in need. If you’re motivated by a desire to make a positive impact, then we want to talk to you!
We are seeking an AI Engineer who is passionate about machine learning (ML), natural language processing (NLP), and conversational AI. You will be responsible for developing and fine-tuning cutting-edge AI-powered solutions, including a Conversational AI Assistant, reviews clustering model, and vector database. You’ll work closely with product management, data science, and the engineering team to develop AI-driven solutions that enhance business processes, improve customer experiences, and provide valuable insights.
Our culture is built on the foundation of thinking disruptively, obsessing over adding value, and reaching out to support one another as we strive to Make Giving Simple and have fun doing it! Our small, tight-knit team is seeking a candidate who will work closely with us at our Downtown Boston headquarters. We work best when we can all innovate together in an open, collaborative environment.
Click to learn how Resupply is forever changing charitable giving: ReSupply Explainer Video (https://www.youtube.com/watch?v=AVW60dsKJq0&t=6s)

QUALIFICATIONS:

• Bachelor’s degree in Computer Science, Engineering, or a related field
• Hands-on experience in AI, machine learning, and NLP development
• Proficiency in Python, with experience in TensorFlow, PyTorch, or Hugging Face Transformers
• Experience with a variety of tree-based models such as XGBoost and Random Forests
• Familiarity with LLM fine-tuning and prompt engineering
• Experience using AI/ML APIs (OpenAI, Anthropic, Google Bard, Whisper, etc.)
• Experience with Conversational AI development platforms (e.g., Rasa, Dialogflow, Botpress, etc.)
• Experience with vector database architecture and libraries (FAISS, Pinecone, Sentence Transformer)
• Familiarity with cloud platforms (AWS, Google Cloud, Azure) for deploying AI models
• Familiarity with SQL databases and querying languages, such as PostgreSQL and Amazon Redshift
• Experience with clustering models, sentiment analysis, and data-driven decision-making
• Excellent problem-solving skills and attention to detail
• Ability to work in an agile environment with cross-functional teams
• Strong communication skills and the ability to explain technical concepts to non-technical stakeholders
• Understanding of data privacy regulations and best practices for secure AI systems
  ReSupply is an equal opportunity employer. As such, it is our policy to fill positions with qualified candidates regardless of the candidate’s race, color, sex, age, religion, ancestry, national origin, citizenship status, marital status, sexual orientation, gender identity, genetic information, disability, pregnancy, military status, veteran status or any other protected group status

• Design, develop, and deploy a Conversational AI Assistant for inbound sales and customer support use cases
• Implement Natural Language Processing (NLP) and Machine Learning (ML) techniques to enhance the AI Assistant’s performance and understanding
• Collaborate with cross-functional teams (Product, Data Science, Engineering, Customer Success) to gather requirements and define the AI Assistant’s capabilities
• Continuously improve the AI Assistant’s understanding, accuracy, and user interaction based on feedback and data analysis
• Refine a vector database and its interface storing insightful data on charitable contributions collected through our system
• Use sentiment analysis to analyze customer reviews and give data-driven suggestions to improve our user experience
• Integrate the AI Assistant with backend systems, databases, and APIs to ensure seamless customer interactions
• Stay up-to-date with the latest advancements in AI and NLP technologies
• Create and fine-tune review clustering models to provide insights into customer sentiment and improve customer support operations
• Monitor the performance of all AI-driven solutions, identify areas for optimization, and apply techniques for improving efficiency and user satisfaction