Our client, a cutting-edge deep-tech AI platform in the MENA region, is seeking a Senior/Lead Machine Learning Engineer. [This role requires relocation to Riyadh, KSA] As a Senior Machine Learning (AI) Engineer, you will design, develop, and deploy advanced machine learning solutions across various domains, including NLP, LLMs, Recommender engines, and Anomaly detection. This role involves end-to-end project ownership, from data preprocessing to the creation of service APIs, and offers opportunities to work on cutting-edge AI technologies. You will be responsible for Mentoring junior team members, sharing knowledge, and advising on the best machine learning and software engineering practices and approaches. Establishing and maintaining robust communication channels with other cross-functional teams to facilitate the integration of machine learning solutions into other Unifonic products. Developing and optimizing highly confident machine learning algorithms and models and creating/exposing the service APIs using frameworks such as Flask, FastAPIs, or other relevant frameworks. Staying up-to-date with the latest machine learning research papers, as well as AI trends (i.e., Generative AI). Collaborating with the data engineering team and other teams to collect and analyze extensive datasets, extracting insights and patterns in real-time, near-real-time, or batch processing mode. Implementing proof of concepts and prototypes to demonstrate the potential of new AI use cases and innovations. Building scalable, maintainable machine learning services that should handle thousands of requests per second and help perform the required load tests to meet the SLA. The Must-Haves 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 the best software engineering fundamentals, i.e. data structures, algorithms, and data modelling 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 requires 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, modelling and optimization, evaluation metrics, classification, and clustering. Experience with LLM frameworks (i.e. LangChain) and prompt engineering techniques.
