AI Engineer

Location: Remote Type: Full-time Experience: 3+ Years Salary: up to 70K/Month based on experience Role Summary We are looking for a hands-on AI Data Engineer who can independently manage end-to-end data workflows, including data collection, document processing, dataset preparation, retrieval pipelines, model fine-tuning, and data visualization. This role requires strong technical skills across Python, automation, ML tooling, and analytical reporting. Key Responsibilities (Technical)1. Data Acquisition & Automation - Build automated data collection workflows using tools such as Firecrawl, Playwright, Scrapy, or similar frameworks - Extract multi-format documents (PDFs, HTML, text, images) - Handle large-scale crawling, rate limits, error handling, and scheduling 2. Document Processing & Transformation - Clean and process unstructured documents - Apply OCR (Tesseract, PaddleOCR) for scanned files - Convert and structure data using PyPDF2, pymupdf, BeautifulSoup, etc. - Prepare data in formats such as JSON, JSONL, or CSV 3. Dataset Preparation - Segment and structure text for ML training - Create Q&A datasets, summaries, instruction-response pairs, and labeled text - Build high-quality datasets compatible with fine-tuning frameworks 4. Retrieval & Indexing Pipelines - Implement document chunking strategies - Generate embeddings and manage vector databases (Qdrant, Pinecone, Weaviate) - Build retrieval workflows using LangChain or LlamaIndex - Optimize retrieval accuracy and latency 5. Model Training & Fine-Tuning - Run fine-tuning jobs using HuggingFace Transformers, LoRA/QLoRA, or similar methods - Monitor training performance and refine datasets - Package and deploy fine-tuned models 6. Data Visualization & Analytics - Create analytical charts, trends, and insights using: - Pandas - Matplotlib - Seaborn - Plotly - Build simple internal dashboards or visual summaries for reports - Transform raw datasets into meaningful visual insights 7. Automation & Infrastructure - Write modular, maintainable Python scripts - Containerize workflows with Docker - Maintain version control with Git - Ensure reproducibility and pipeline stability Required Technical Skills - Strong proficiency in Python - Experience with Firecrawl, Playwright, Scrapy, or similar tools - Strong background in document parsing, text processing, and OCR - Familiarity with LangChain or LlamaIndex - Experience with vector databases - Hands-on experience with HuggingFace, Transformer models, and fine-tuning - Ability to write clean, efficient data pipelines - Experience with Matplotlib, Seaborn, Plotly, or other visualization tools - Comfort using Docker and Git Nice to Have - Experience serving models or building small APIs (FastAPI) - Exposure to GPU training environments - Background in large-scale unstructured data work - Ability to create lightweight dashboards (Plotly Dash, Streamlit) Ideal Candidate - Comfortable owning full pipelines independently - Detail-oriented and analytical - Strong problem-solving ability - Can work with minimal supervision - Enjoys building structured systems from scratch