Machine Learning Engineer

aspire; Abu Dhabi; On-site; AED 120,000 - 150,000; Full time

Job summary

Aspire is seeking a Machine Learning Engineer to develop intelligent systems for document understanding. You will design, develop, and deploy machine learning models, focusing on data extraction from complex documents. The role requires collaboration with cross-functional teams and a solid background in Python and deep learning frameworks.

Qualifications

• 3-4 years of professional experience in Python development.
• Experience with deep learning frameworks.

Responsibilities

• Design and implement intelligent document processing pipelines.
• Research and apply state-of-the-art deep learning models.
• Deploy models and ML pipelines to cloud infrastructure.

Skills

Python

Deep Learning

Natural Language Processing

Problem Solving

Analytical Thinking

Communication

Education

Bachelor's degree in Computer Science

Bachelor's degree in Engineering

Bachelor's degree in Data Science

Tools

PyTorch

TensorFlow

Keras

SQL

Hugging Face

Job description

As a Machine Learning Engineer at Aspire, you will play a key role in building intelligent systems that automate and optimize document understanding processes. You will be responsible for designing, developing, and deploying machine learning models focused on extracting structured data from complex, unstructured documents. Your skills in Python, deep learning, and natural language processing will help power intelligent automation solutions used across global financial operations.

About the Job

As a Machine Learning Engineer at Aspire, you will play a key role in building intelligent systems that automate and optimize document understanding processes. You will be responsible for designing, developing, and deploying machine learning models focused on extracting structured data from complex, unstructured documents. Your skills in Python, deep learning, and natural language processing will help power intelligent automation solutions used across global financial operations.

What you'll do

1. Design and implement intelligent document processing pipelines using a blend of machine learning and rule-based methods.
2. Research and apply state-of-the-art deep learning models (e.g., transformers) for document parsing and semantic understanding.
3. Develop and fine-tune large language models (LLMs) for tasks such as information extraction, table detection, and document classification.
4. Build robust data validation frameworks to ensure accuracy and reliability of extracted information.
5. Convert complex document formats into structured data while preserving context and content fidelity.
6. Deploy models and ML pipelines to cloud infrastructure using tools like Docker and AWS services.
7. Evaluate model performance through experiments, track key metrics, and communicate results to stakeholders.
8. Participate in Agile development processes including sprint planning, daily stand-ups, and retrospectives.
9. Collaborate with cross-functional teams including engineers, product managers, and domain experts.

What you'll need

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related discipline.
• 3-4 years of professional experience in Python development, with a focus on data extraction and ML applications.
• Experience with deep learning frameworks such as PyTorch, TensorFlow, or Keras.
• Familiarity with transformer-based architectures and LLMs for NLP and document processing tasks.
• Proficiency in using the Hugging Face ecosystem (Transformers, Datasets, Model Hub).
• Solid SQL skills for querying and managing structured data.
• Strong problem-solving and analytical thinking skills.
• Excellent communication skills for translating technical concepts to non-technical audiences.
• Experience working in Agile/Scrum teams.
• Awareness or knowledge of IT security best practices as defined by ISO/SOC or similar.