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Nvidia Senior Data Scientist 
Israel, North District 
896724669

31.07.2024

What you’ll be doing:

  • Develop and implement machine learning & deep learning models: Design research, develop, and deploy scalable models and algorithms that address complex business challenges in the manufacturing process. Apply various techniques such as supervised and unsupervised learning.

  • Data pre-processing and analysis: Collaborate with data scientists and data engineers to collect, clean, pre-process, and transform large and wide datasets. Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the model performance.

  • Model evaluation and optimization: Conduct detailed model evaluation metrics and validation to ensure accuracy, reliability, and scalability. Optimize model performance by fine-tuning hyper parameters, feature engineering, and applying techniques such as ensemble learning and continuous learning.

  • Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure flawless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.

  • Collaborate with multidisciplinary teams: Collaborate with product engineers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

What we need to see:

  • Master’s degree in Computer Science, Information Systems, Engineering, Statistics, or a related field.

  • 5+ years of experience as a data scientist or a similar role, with a consistent record of successfully delivering ML / DL solutions.

  • Demonstrated expertise in conducting clustering research.

  • Experience with training models over tabular data.

  • Strong programming skills in languages such as Python, R, or Java. Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.

  • Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib.

  • Deep understanding of machine learning algorithms, statistical models, and data structures.

  • Familiarity with software development practices and version control systems (e.g., Git).

  • Experience with experimental design, A/B testing, and evaluation metrics for ML models.

Ways to stand out from the crowd:

  • Strong analytical thinking and problem-solving abilities, with a focus on applying ML techniques to real-world challenges.

  • Ability to analyze complicated and wide data sets, identify patterns, and derive significant insights.

  • Experience with Large Language Models (LLM) and Natural Language Processing (NLP).

  • Proficient in training Reinforcement Learning models.

  • Skilled in developing and conducting research in computer vision.

  • Self-motivated with a goal to stay updated on the latest methodologies and machine learning technologies.