ADAS Data Science & Machine Learning Engineer

Role Overview: As an ADAS Data Science & Machine Learning Engineer at ZF, your primary responsibility will be to develop designs and scale AI-based solutions in the ADAS field. You will be involved in the evaluation and implementation of modern generative AI models such as LLM-based generators, diffusion models, and GANs. Your role will also include generating synthetic data using artificial intelligence for existing and future software-in-the-loop and hardware-in-the-loop test benches (SiL/HiL). It will be your responsibility to ensure that AI and LLM-based solutions are applicable for development, and adequate training methodologies are provided for their implementation. You will be at the forefront of utilizing state-of-the-art AI models in the field. Key Responsibilities: - Develop designs and scale AI-based solutions in the ADAS field - Evaluate and implement modern generative AI models like LLM-based generators, diffusion models, GANs - Generate synthetic data using artificial intelligence for SiL/HiL test benches - Ensure the applicability of AI and LLM-based solutions for development - Provide adequate training methodologies for AI model implementation Qualifications Required: - Bachelors or Masters degree in Computer Science, Software Engineering, or equivalent experience - Knowledge of artificial intelligence including large language models, neural network training, and world foundation models, as well as sensor data like camera, LiDAR, radar, etc. - Minimum of 3 years of professional experience in driver assistance systems or autonomous driving functions - High interest in the newest technologies and development trends related to neuronal networks, AI, agentic AI, etc. - Self-driven and motivated individual who continuously builds up knowledge in the fast-moving field Note: Contact Veerabrahmam Darukumalli to be part of the ZF team as an ADAS Data Science & Machine Learning Engineer and apply now! Role Overview: As an ADAS Data Science & Machine Learning Engineer at ZF, your primary responsibility will be to develop designs and scale AI-based solutions in the ADAS field. You will be involved in the evaluation and implementation of modern generative AI models such as LLM-based generators, diffusion models, and GANs. Your role will also include generating synthetic data using artificial intelligence for existing and future software-in-the-loop and hardware-in-the-loop test benches (SiL/HiL). It will be your responsibility to ensure that AI and LLM-based solutions are applicable for development, and adequate training methodologies are provided for their implementation. You will be at the forefront of utilizing state-of-the-art AI models in the field. Key Responsibilities: - Develop designs and scale AI-based solutions in the ADAS field - Evaluate and implement modern generative AI models like LLM-based generators, diffusion models, GANs - Generate synthetic data using artificial intelligence for SiL/HiL test benches - Ensure the applicability of AI and LLM-based solutions for development - Provide adequate training methodologies for AI model implementation Qualifications Required: - Bachelors or Masters degree in Computer Science, Software Engineering, or equivalent experience - Knowledge of artificial intelligence including large language models, neural network training, and world foundation models, as well as sensor data like camera, LiDAR, radar, etc. - Minimum of 3 years of professional experience in driver assistance systems or autonomous driving functions - High interest in the newest technologies and development trends related to neuronal networks, AI, agentic AI, etc. - Self-driven and motivated individual who continuously builds up knowledge in the fast-moving field Note: Contact Veerabrahmam Darukumalli to be part of the ZF team as an ADAS Data Science & Machine Learning Engineer and apply now!