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23902 - Data Scientist - GenAI at QualityAI · Trevo
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Job Description
About the role
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.
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 Generative AI solutions, such as RAG pipelines and LLM-based systems, including locally hosted / on-premise LLM deployments for privacy-sensitive environments.
It also includes additional work in classical Machine Learning and Data Science.
The position includes designing, deploying, and integrating AI solutions in highly secured local and air-gapped environments, working with embeddings and latent space representations to build effective retrieval and LLM-based systems, and participating in technical discussions and pre-sales activities.
This full-time position is in Lod and requires security clearance.
What you'll do
Deploy scalable solutions using Docker, cloud platforms (AWS/GCP/Azure), and Win/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.
Deploy and serve open-source LLMs locally (e.g., Ollama, vLLM), including model selection, quantization, and hardware/performance trade-offs.
Build and optimize embedding-based retrieval in latent space: select and evaluate embedding models, design chunking strategies, and apply hybrid search and reranking to improve retrieval quality.
Integrate LLM APIs (cloud and local) and vector databases, and optimize GenAI system performance.
Requirements
2+ years of experience in Machine Learning / Data Science, with hands-on experience delivering end-to-end GenAi solutions in production environments.
B.A. or M.A. in Computer Science, Data Science, Statistics, Mathematics, or a related field.
Proficiency in Python and common ML\DL\GenAi libraries.
Experience with RAG systems and LLM-based solutions.
Solid understanding of embeddings and vector representations (latent spaces), including semantic similarity and vector search.
Hands-on experience running open-source LLMs locally (Ollama or similar).
Experience with Docker and cloud environments.
Experience working in client-facing environments.
Ability to pass a security clearance process (required).
Work on-site at the client's offices.
M.A. or Ph.D. in a relevant field.
Experience with Kubernetes, CI/CD, or MLOps.
Experience monitoring GenAI solutions in production.
Experience with vector databases (e.g., Qdrant, Chroma, pgvector) and RAG evaluation frameworks.
Experience with on-premises or air-gapped AI deployments.
Experience presenting technical solutions to clients (English and Hebrew).
Why should you join us?
Grow your career in a stable, innovative environment
Collaborate closely with clients to deliver smart, high-quality solutions
Make an impact in a dynamic, learning-driven environment
Be part of a human, value-driven organization that cares