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.
Benefits & Compensation
- Competitive salary and bonus.
- Unifonic share scheme.
- 30 holiday days after the first anniversary.
- Your Birthday off!
- Spend up to 25 days per year working from anywhere in the world.
- Paid leave for new parents.
- LinkedIn learning license.
Work Mode
This role is based locally in Cairo, Al Qāhirah, Egypt.
Unifonic is an equal opportunity employer.
