Senior AI/ML Engineer
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the organization of the first Data Science UA conference, setting the foundation for our growth. Over the past 9 years, we have diligently fostered the largest Data Science Community in Eastern Europe, boasting a network of over 30,000 AI top engineers.
About the client:
We are working with a new generation of data service provider, specializing in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organizations. The company’s data-driven services are built upon the deep AI expertise the company’s acquired with a 1000+ client base around the globe. The company has 1000 employees across 20 offices who are focused on accelerating digital transformation.
About the role:
We are looking for an AI/ML Engineer (LLM, RAG), who will join the big enterprise project in Abu-Dhabi. It will be 6+ months on-site collaboration with one of the major clients with a great chance to expand work further.
Required skills:
– 6+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP.
– Advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.
– Experience with VLLMs, LLMs, SLMs, Knowledge RAG, Graph RAG.
– Experience with Vector DBs, Graph DBs.
– Proficiency in prompt engineering, Model Fine-tuning/Distillation, Agentic AI Modeling.
– Proficiency in Python and common data science and NLP libraries (pandas, NumPy, scikit-learn, spaCy, NLTK, langdetect, fasttext).
– Strong experience with deep learning frameworks such as PyTorch or TensorFlow for building NLP models.
– Experience deploying machine learning models in production (e.g., using REST APIs or batch pipelines) and integrating with real-world applications.
– Experience working in a collaborative, cross-functional environment and strong communication skills.
As a plus:
– Familiarity with MLOps concepts and tools (version control for models/data, CI/CD for ML).
– Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training.
Responsibilities:
– Develop and maintain AI applications.
– Design, develop, and implement AI models, integrate them into software applications
– Сollaborate with data scientists to transform data science prototypes into high-quality software products.
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