AI & Machine Learning Engineer

algoleap

Website: algoleap.com
Job details:
Key Responsibilities

AI / ML & Document Intelligence

• Design and implement AI/ML solutions for document abstraction, classification, and information extraction from structured and unstructured documents (PDFs, scanned files, Office documents). - Develop and optimize NLP, OCR, and transformer-based models for entity extraction, classification, and summarization. - Build end-to-end document processing pipelines integrating OCR, ML inference, and post-processing rules. - Continuously evaluate and improve model accuracy, performance, and reliability.
  
  

Software Engineering

• Develop clean, efficient, and scalable Python code following engineering best practices. - Build and maintain RESTful APIs and microservices (e.g., FastAPI or similar frameworks). - Ensure code quality through unit testing, logging, error handling, and observability. - Collaborate with frontend teams (Angular/SPA or equivalent) for AI service integration.
  
  

Analytical & Problem Solving

• Analyze complex document layouts, content variability, and edge cases. - Perform data exploration, feature engineering, and root-cause analysis of model failures. - Translate business requirements and document rules into effective ML-based solutions.
  
  

Collaboration & Communication

• Work closely with product managers, architects, data engineers, and business stakeholders. - Clearly explain AI model behavior, outputs, trade-offs, and limitations to non-technical audiences. - Contribute to design reviews, sprint planning, demos, and technical documentation.
  
  

Required Qualifications

Technical Skills

• Strong proficiency in Python for data processing, ML development, and API building. - Strong knowledge and hands-on experience with Large Language Models (LLMs). - Experience building applications using Retrieval-Augmented Generation (RAG) patterns. - Hands-on experience with prompt engineering and optimizing LLM outputs. - Solid understanding of Machine Learning, NLP, and information extraction techniques. - Hands-on experience with ML frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, spaCy, Transformers, or equivalent. - Experience working with OCR and document AI workflows. - Familiarity with cloud-native development and REST-based architectures. - Working knowledge of databases (SQL/NoSQL) and data pipelines.
  
  

Analytical Skills

• Strong analytical thinking and structured problem-solving ability. - Ability to understand and model complex document structures and patterns. - Experience measuring model performance using both technical and business-oriented metrics.
  
  

Communication & Professional Skills

• Strong verbal and written communication skills. - Ability to collaborate effectively in cross-functional teams. - Comfortable presenting technical ideas and AI outcomes to diverse audiences.
  
  

Preferred / Nice To Have

• Experience with cloud AI platforms (Azure, AWS, or GCP). - Exposure to MLOps, model deployment, monitoring, and lifecycle management. - Familiarity with vector databases and embedding-based search. - Familiarity with security, authentication, and enterprise data governance standards. - Experience working in Agile / Scrum environments.

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