Data Scientist

Why Argus?

- You can be part of a leading company in the automotive industry
- You can help save lives
- You can work with cool challenging technology
- You can make an impact and help change the world

Job Location: Tel Aviv

Job Description:

- Lead the development and deployment of Large Language Models (LLMs), as the primary expert, ensuring optimal performance, scalability, and practical application within the organization, setting a precedent for innovation and excellence.
- Implement advanced techniques for LLM training, including parameter efficient fine-tuning, and optimization for cost-effectiveness and response speed.
- Define and establish metrics for evaluating LLM performance, including accuracy, bias, and real-time responsiveness, driving continuous improvement and innovation.
- Develop generative AI capabilities utilizing varied big data sources to extract detailed textual and graphical insights, paving the path for pioneering data exploration and analysis.
- Architect, design, and deploy anomaly detection models for real-time monitoring of vehicle data streams, encompassing all stages from data preprocessing to model deployment in production.
- Collaborate closely with cross-functional teams to integrate data science solutions seamlessly into existing infrastructure, driving efficiency and reliability.
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- Take ownership of research and development initiatives, identifying opportunities for advancement and proposing innovative solutions to address complex challenges.

REQUIREMENTS

- Bachelor’s degree in Computer Science, Electrical Engineering, or related field, with a minimum of 5 years of experience in data science.
- Proficiency in Python programming and deep understanding of machine learning and deep learning techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers.
- Hands-on experience with training and fine-tuning LLMs.
- Strong background in MLOps workflows, including versioning of datasets, and experience with platforms such as MLFlow.
- Proven track record of deploying machine learning models in production environments, with a keen focus on scalability, reliability, and performance optimization.
- Expertise in anomaly detection methodologies and real-time streaming analytics, with a demonstrated ability to architect and implement end-to-end solutions.
- Excellent communication and collaboration skills, with the ability to thrive in a fast-paced, dynamic environment and drive initiatives independently.