Nvidia Software AI Engineer 

Israel, North District 

971579733

What you’ll be doing:

• Build and maintain data pipelines and ETL flows for logs, telemetry, and hardware test data supporting AI/ML workflows.

• Prepare, clean, and structure large, complex datasets (structured & unstructured) to train and fine-tune LLMs.

• Assist in developing and deploying LLM-based applications for root cause analysis and hardware debugging.

• Experiment with prompt engineering, retrieval-augmented generation (RAG), and vector search to integrate knowledge into models.

• Collaborate with hardware, reliability, and AI platform teams to embed intelligent debugging tools into NVIDIA’s engineering ecosystem.

• Monitor and evaluate model performance, ensuring accuracy, scalability, and reliability in production environments.

What we need to see:

• B.Sc. or M.Sc. in Computer Science, Electrical/Computer Engineering, Data Science or related field (or equivalent practical experience).

• 2+ years of industry experience in machine learning or data engineering.

• Strong programming skills in Python (pandas, NumPy, PyTorch or TensorFlow).

• Proficiency with SQL and modern data pipeline tools.

• Understanding of deep learning fundamentals and strong interest in LLMs/NLP.

• Hands-on experience with Linux environments, version control (Git), and container tools (e.g., Docker).

• Strong analytical and problem-solving skills

• Eagerness to learn complex hardware/software systems.

Ways to stand out from the crowd:

• Internship or project experience with LLM fine-tuning, prompt engineering, or retrieval-augmented generation.

• Exposure to hardware debugging,observability/loggingsystems, or chip/system reliability analysis.

• Experience with vector databases (FAISS, Pinecone, Milvus) or MLOps tools (MLflow, Kubeflow).

• Master’s degree in a related field (e.g., Computer Science, Electrical Engineering, Data Science), showing advanced theoretical foundation and research exposure.