AI/ML Engineer

JOB OVERVIEW

We are seeking an AI/ML Engineer to develop core AI functionalities for an AI-driven grant discovery and application platform. This role focuses on data extraction, grant matching algorithms, NLP-based funder intelligence, and AI-assisted grant writing. The engineer will work on semantic search, data enrichment, and AI-driven document processing, ensuring that nonprofits and corporate clients can efficiently identify and apply for relevant grants.

Our client is a US-based technology company dedicated to helping nonprofit organizations and select corporate clients (eBay, Adobe, Robert Half) leverage AI for operational efficiency and impact. The mission is to align AI technology with grant-seeking processes, ensuring streamlined and effective funding applications.

AS AN AI/ML Engineer, YOU’LL HAVE THE RESPONSIBILITIES:

1. Grant Matching & Recommendation AI

• Develop semantic search models using vector embeddings (FAISS, Pinecone, Weaviate).
• Implement eligibility filtering based on structured grant data (funding criteria, geography, eligibility).
• Build AI ranking models to score grant relevance using NLP-based similarity metrics.
• Ensure explainability in AI grant matching decisions for transparency.

2. Data Collection & Extraction

• Automate grant data collection via APIs (Candid.org, Grants.gov) and web scraping (if necessary).
• Implement text extraction from grant documents (OCR, NLP-based parsing, PDF/HTML/XML processing).
• Structure funding opportunities into a normalized database for efficient querying.
• Develop crawlers and automated bots to extract funder details from external sources.

3. Grant & Funder Intelligence

• Build NLP pipelines to extract key funder insights (mission statements, past funding history).
• Develop models for grant clustering & categorization based on funding themes.
• Automate trend analysis of past awarded grants to refine AI-driven recommendations.
• Implement LLM-based summarization for grant/funder profiles.

4. AI-Assisted Grant Writing

• Generate structured proposal templates based on grant-specific requirements.
• Autofill low-complexity sections (organization details, mission statement, past funded projects).
• Implement retrieval-augmented generation (RAG) to personalize proposal content.
• Ensure AI-generated proposals align with specific grant formatting guidelines.
• Allow user-in-the-loop editing, enabling refinements before submission.

5. API & Backend Integration

• Develop AI-powered APIs for grant search, ranking, and proposal generation.
• Implement AI agent pipelines (e.g., research agent, grant writer agent).
• Work closely with Full-Stack Developer to ensure smooth AI integration into the PoC system.
• Support document generation APIs for outputs in Google Docs, MS Word, or Excel.

6. Performance Optimization & Scalability

• Optimize AI inference speed for near-instant grant matching.
• Reduce processing latency for NLP-based proposal generation.
• Implement asynchronous processing for long-running AI tasks.
• Monitor AI model drift and ensure continuous improvements.

KNOWLEDGE, SKILLS, COMPETENCIES, AND EXPERIENCE:

1. AI/NLP Expertise

• Semantic Search (Vector Embeddings, FAISS, Pinecone, Weaviate)
• Named Entity Recognition (NER) & Text Classification (spaCy, NLTK, Hugging Face Transformers)
• OCR & NLP-based document parsing (Tesseract, LayoutLM, PyMuPDF)
• Summarization & Intelligent Text Generation (LLMs, GPT, BERT, Retrieval-Augmented Generation)

2. Machine Learning & Software Development

• Programming: Python (LangChain, PyTorch, TensorFlow)
• ML Frameworks: OpenAI API, Hugging Face Transformers, Vector Search Engines
• Database Management: SQL, NoSQL, Elasticsearch, Vector Databases

3. API Development & AI Deployment

• Data Integration & Extraction via REST APIs (handling JSON, XML, structured/unstructured formats)
• Containerized Deployment: Docker, serverless AI processing (AWS Lambda, Google Cloud Functions)
• AI Performance Optimization: Reduce inference times & optimize large-scale NLP models

BONUS POINTS IF YOU HAVE:

• Experience working on AI-powered search and content automation platforms
• Familiarity with LLM fine-tuning for domain-specific applications
• Understanding of cloud-based AI services (AWS SageMaker, Google Cloud AI)
• Knowledge of Python-based web frameworks (FastAPI, Flask) & web scraping/data extraction (BeautifulSoup, Scrapy, Selenium)
• Prior experience with document processing automation and compliance-driven AI solutions

CLIENT AND DOMAIN:

• Client: A US-based software company providing AI-driven solutions for nonprofits and corporations.
• Domain: NLP, AI Intelligence & Automation