23001 - Data Scientist

QualityAI is the leading AI-first quality engineering company. We deliver end-to-end quality management services across the business and technology life cycle for enterprise customers who need certainty at Go-Live. 

 We build and test services and products using AI, working across data, models, platforms, devices, and infrastructure to ensure those systems perform as expected at scale 

Your next career move starts here: Data Scientist – Netanya

We are looking for a hands-on Data Scientist to join our AI delivery team and build end-to-end AI solutions for enterprise clients.

The role focuses mainly on work on Generative AI solutions such as RAG pipelines and LLM-based systems with additional work on Classical Machine Learning and Data Science. The position includes designing, deploying, and integrating AI solutions across diverse client environments and participating in technical discussions and pre-sales activities.

Responsibilities:

• Deploy scalable solutions using Docker, cloud platforms (AWS/GCP/Azure), and Linux environments, in collaboration with DevOps teams.
• Design and deploy end-to-end ML\DL\GenAI solutions, including data analysis, feature engineering, model development, and performance monitoring.
• Apply AI algorithms and conduct statistical analysis on structured and unstructured data.
• Develop Generative AI solutions, including RAG pipelines and LLM-based applications.Integrate LLM APIs and vector databases and optimize GenAI system performance.

Requirements:

• +3 years of experience in Machine Learning / Data Science, with hands-on experience delivering end-to-end ML solutions and working with cloud-based production environments.
• B.A. or M.A. in Computer Science, Data Science, Statistics, Mathematics, or related field.
• Proficiency in Python and common ML libraries.
• Experience with RAG systems and LLM-based solutions.
• Experience with Docker and cloud environments.
• Experience working in client-facing environments.
• M.A or Ph.D. in relevant fields. - Advantages.
• Experience with Kubernetes, CI/CD, or MLOps.  - Advantages.
• Experience monitoring ML models in production.  - Advantages.
• Experience presenting technical solutions to clients ( English and Hebrew)  - Advantages.