About Alaan
We are an AI-powered expense management platform designed to simplify finance for businesses in the Middle East, helping them save both time and money. Our platform offers everything businesses need to manage and control their expenses in one place, including smart corporate cards, AI-powered automation and insights, streamlined accounting, and centralized dashboards.
Since 2022, over 1000 businesses in the UAE—from startups to enterprises like Al Barari, Rove, Rivoli, Punjab National Bank, and CarSwitch—have used Alaan to control their spending and reduce costs. Together, our customers have saved over AED 100 million using Alaan.
About the role
As a Machine Learning Engineer, you will play a key role in designing, building, and fine-tuning machine learning models that drive critical business outcomes. Leveraging cutting-edge technologies, including open-source models, you’ll address complex challenges such as extracting structured information from unstructured data (e.g., receipts, invoices) and improving the performance of AI systems. This is an exciting opportunity to build impactful solutions at the intersection of AI and business.
What you'll do
- Model Development
- Fine-tune open-source models (e.g., Huggingface) including SLMs, LLMs, and VLMs using QLoRA and PEFT methodologies.
- Design and develop classical machine learning models for tasks like classification, extraction, NER, and clustering.
- Data Engineering
- Preprocess, clean, and label large datasets to prepare them for model training.
- Develop and maintain pipelines on data warehouses for efficient data handling and feature extraction.
- Deployment and Optimization
- Deploy models in production environments with a focus on scalability and low latency.
- Optimize inference performance through techniques such as model quantization, pruning, and distillation.
- Build and prototype GenAI applications using frameworks like Langchain and LlamaIndex.
- Performance Monitoring
- Monitor AI system performance using observability platforms.
- Evaluate models using metrics like precision, recall, and F1-score.
- Address failure cases by retraining models or refining data pipelines.
- Collaboration
- Work with data scientists, product managers, and software engineers to integrate models into the product stack.
- Collaborate with cross-functional teams to define requirements and iterate on solutions.
What we are looking for
- Educational Background
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
- Technical Skills
- Proficiency in Python (mandatory) and frameworks like PyTorch, TensorFlow, Transformers, and Scikit-learn.
- Experience with NLP tools (e.g., spaCy, NLTK) and OCR libraries (e.g., Tesseract, EasyOCR).
- Strong understanding of machine learning algorithms and concepts, including supervised/unsupervised learning, deep learning, and transfer learning.
- Familiarity with deploying models on cloud platforms (AWS, GCP, Azure) or edge devices.
- Knowledge of MLOps practices, including CI/CD pipelines for ML models.
- Experience
- Hands-on experience with fine-tuning and deploying LLMs or similar models using SFT, PEFT, QLoRA, or RLHF techniques.
- Understanding of the GenAI tech stack for RAG pipelines and computer vision applications.
- Proficiency in handling data using SQL and NoSQL databases.
- Experience in model evaluation and error analysis.
- Preferred Skills
- Experience with document data extraction (e.g., receipts, invoices, contracts).
- Knowledge of data annotation tools (e.g., Label Studio, Prodigy).
- Experience integrating external APIs and developing ML-based RESTful APIs.
What's in it for you
- Contribute to building the Middle East’s most beloved fintech brand from the ground up
- Benefit from a role with significant ownership and accountability
- Thrive in a flexible hybrid culture with ample work-life balance
- Participate in exciting offsite events
- Competitive salary and equity
- Enjoy additional perks like travel allowances, gym memberships, and more
