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.

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.