Unifonic is looking for a Senior Machine Learning Engineer to join our Products & Engineering department. You will be responsible for designing, developing, and deploying advanced machine learning solutions across NLP, Text Classification, RAG, LLMs, Recommender engines, and Anomaly detection. This role offers end-to-end project ownership, from data preprocessing to creating service APIs, within a dynamic SaaS environment revolutionizing business communication.

What You'll Do

Lead the end-to-end design, development, and deployment of robust and scalable machine learning solutions, with a strong emphasis on NLP and RAG architectures.
Architect and implement RAG systems, combining large language models with robust retrieval mechanisms.
Apply advanced NLP techniques for tasks such as text classification, entity recognition, sentiment analysis, summarization, question answering, and information extraction.
Research, evaluate, and integrate state-of-the-art NLP models and RAG frameworks.
Mentor junior team members, sharing knowledge and advising on best machine learning and software engineering practices.
Establish and maintain robust communication channels with other cross-functional teams to facilitate the integration of machine learning solutions.
Develop and optimize machine learning algorithms and models and create/expose service APIs using frameworks such as Flask or FastAPI.
Stay up to date with the latest machine learning research papers and AI trends.
Collaborate with the data engineering team to collect and analyze extensive datasets, extracting insights and patterns in real-time, near-real-time, or batch processing mode.
Implement proof of concepts and prototypes to demonstrate the potential of new AI use cases and innovations.
Build scalable, maintainable machine learning services capable of handling thousands of requests per second and perform required load tests.
Review the code of other team members and suggest improvements to ensure SOLID principles and clean architecture.
Assist in project documentation and demos.

What We're Looking For

Proven experience designing and implementing RAG systems, including familiarity with various retrieval strategies and knowledge graph integration.
Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar tools for building and managing autonomous agents.
Deep expertise in various NLP techniques and models, including Transformer architectures, Large Language Models and their fine-tuning/adaptation, Vector embeddings and similarity search, Text classification, named entity recognition, sentiment analysis, summarization, and question answering.
3-5 years of relevant work experience as a Machine Learning Engineer.
3+ years of experience with Python.
Excellent analytical abilities, with the capacity to collect, organize, and analyze large datasets to glean valuable insights.
End-to-end experience in training, evaluating, testing, and deploying machine learning products in production.
Ability to write world-class code in Python, considering best software engineering fundamentals.
Solid experience in ML frameworks such as NumPy, Pandas, Scikit-Learn, PyTorch, Keras, BERT, Tensorflow, and similar.
Familiarity with MLOps best practices, e.g., Model deployment and reproducible research.
Mastering data science skills like SQL, hypothesis testing, data cleansing, data augmentation, data pre-processing techniques, and dimensionality reduction.
Excellent understanding of Machine learning techniques like Naive Bayes classifiers, SVM, Decision Tree, KNN, K-means, Random Forest, modeling and optimization, evaluation metrics, classification, and clustering.
Experience with the Hugging Face libraries.
Experience fine-tuning pre-trained models and using vector search to enhance LLMs results.
Familiar with code versioning tools such as GIT, CI/CD concepts, and toolchains.
Familiar with Agile methodologies i.e. scrum and kanban.
Ability to develop high-level architecture and low-level design, end-to-end for a specific project.
A Bachelor’s degree in a relevant field.
Excellent communication and collaboration skills.
Good level of spoken and written Arabic and English.

Nice to Have

Basic knowledge of Kubernetes and Docker.
Experience in event sourcing patterns and tools i.e. Kafka, RabbitMQ, or similar.
General knowledge of Data warehouse tools e.g. Vertica.

Technical Stack

Languages & Core: Python, SQL
ML & Data: NumPy, Pandas, Scikit-Learn, PyTorch, Keras, BERT, Tensorflow
NLP & LLMs: Transformers, GPT, T5, LLama, Mistral, Hugging Face
Frameworks & Tools: LangChain, LangGraph, CrewAI, Flask, FastAPI, GIT
Infrastructure: Kubernetes, Docker, Kafka, RabbitMQ

Team & Environment

You will join our team of 500 Unifones as part of the Products & Engineering department. We are a dynamic startup in the SaaS space with a fun and collaborative work environment where creativity and new ideas are constantly encouraged. Our team is energetic and passionate about delivering the best possible customer experience.