t Alpha7X

Alpha7X is an American technology company building the infrastructure for unified mortgage data. We normalize and reconcile every data field and document to its true Source of Truth, giving stakeholders a single, trusted dataset they can use across the entire loan lifecycle. Our platform eliminates redundant manual review, improves accuracy, and delivers real-time transparency across stakeholders, solving one of the mortgage industry's biggest operational challenges.

We are expanding our engineering presence in Egypt, offering local talent the opportunity to work directly with U.S. enterprise systems and cutting-edge AI orchestration. Our culture values ownership, clarity, teamwork, and action, and we hire people who thrive on solving complex problems at scale.

Role Overview

We’re looking for Machine Learning Engineers who are passionate about LLMs, document AI, and applied research. You’ll work on projects involving model fine-tuning, LoRA adapter training, document classification, OCR post-processing, and AI-driven data extraction from complex financial and legal documents.

You will collaborate closely with the CTO and global engineering teams to design, train, and deploy machine learning models that power our intelligent automation stack.

Key Responsibilities

• Fine-tune large and small language models (LLaMA, Mistral, Gemma, Phi, etc.) for specialized NLP and document-reasoning tasks.
• Develop and optimize LoRA adapters and parameter-efficient fine-tuning (PEFT) workflows.
• Build document classification pipelines to automatically identify and segment mortgage, financial, and compliance documents.
• Integrate AI-aided OCR (e.g., PaddleOCR, Azure Document Intelligence, Tesseract, LayoutLM) for high-accuracy text and table extraction.
• Design evaluation frameworks and metrics for data quality, accuracy, and confidence scoring.
• Collaborate with backend and data engineering teams to deploy models into production (API or microservice environment).
• Research and experiment with new open-source models, embeddings, and multimodal techniques for continuous improvement.

Qualifications

• Bachelor’s or Master’s in Computer Science, AI, Data Science, or related field.
• 2–5+ years of practical experience in machine learning or NLP.
• Strong background in PyTorch, Transformers, PEFT/LoRA, and LangChain or Hugging Face ecosystem.
• Hands-on experience with document AI, OCR, and information extraction.
• Experience deploying ML models as APIs or microservices (FastAPI, Flask, or equivalent).
• Comfortable working with cloud environments (Azure, AWS, or GCP).
• English proficiency sufficient for technical communication with global teams.

Preferred (Bonus) Skills

• Experience with RAG (Retrieval-Augmented Generation) pipelines.
• Familiarity with Vector Databases (e.g., FAISS, Chroma, Milvus).
• Exposure to agentic architectures or workflow orchestration (LangGraph, CrewAI, etc.).
• Experience in MLOps and model versioning/deployment using Docker or Azure ML.

Why Join Us

• Be part of an AI hub built around enterprise-grade document intelligence.
• Work directly with experienced global engineers and researchers.
• Access to cutting-edge infrastructure and compute resources.
• Competitive local salary (based on experience), growth opportunities, and exposure to international projects.

This position will be fully remote for the first few weeks, eventually transitioning to an in-office environment. We are open to hybrid/f

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