Title: Generative AI Engineer Location: Peachtree City, GA 30269 Contract: 6+ Months. Long-term. Industry/Department: Advanced Engineering – Automotive AI/Infotainment Position Summary: Our client is seeking a skilled and forward-thinking Generative AI Engineer to join their Advanced Engineering team. This mid-level role is ideal for professionals with a few years of experience who are passionate about advancing the application of Generative AI and Large Language Models (LLMs) in the automotive domain. The selected candidate will design, develop, and optimize AI solutions to enhance in-vehicle infotainment systems, driver assistance features, and connected car experiences. You will work closely with data scientists, software engineers, and product teams to bring Gen AI-powered prototypes into production. Key Responsibilities: • Design, fine-tune, and evaluate generative AI models for real-world automotive applications such as voice assistants, AI copilots, and smart driver notifications. • Develop prompt engineering strategies and implement natural language understanding pipelines for in-vehicle interaction. • Lead data preparation efforts, including preprocessing and augmenting multimodal datasets (text, audio, telemetry) for model training. • Collaborate with cross-functional teams to integrate LLMs and generative models into infotainment and telematics systems. • Conduct research and feasibility studies on emerging Gen AI technologies to drive innovation in user experience and predictive systems. • Author technical documentation and contribute to AI development standards, tools, and reusable modules. Required Qualifications: Education: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Artificial Intelligence, or related discipline. Experience: • 2–4 years+ of professional experience in machine learning, natural language processing, or generative AI. • Proven contributions to at least one production-level AI/ML system or proof-of-concept deployment. Technical Skills: • Strong Python programming skills and experience with frameworks such as PyTorch or TensorFlow. • Deep understanding of NLP and transformer-based architectures (e.g., BERT, GPT). • Hands-on experience with LLMs or generative AI platforms (e.g., OpenAI, Hugging Face Transformers, LangChain). • Experience working with version control (Git), model evaluation metrics, and ML pipelines. Soft Skills: Strong analytical and problem-solving skills. Ability to manage tasks independently while collaborating effectively across teams. Self-driven, curious, and comfortable navigating ambiguity in early-stage innovation projects. Preferred Qualifications: • Experience with embedded systems or real-time automotive software integration. • Project work or production experience with speech recognition, TTS, or multimodal models. • Knowledge of automotive communication protocols such as CAN, LIN, or Ethernet. • Familiarity with cloud-based AI/ML services (e.g., AWS SageMaker, Azure ML, or GCP Vertex AI). • Awareness of ISO 26262 functional safety and cybersecurity practices relevant to AI systems in vehicles. Summary: The Generative AI Engineer will assist in developing and deploying generative AI models for automotive infotainment, driver assistance, and connected car systems. Key duties include fine-tuning and evaluating LLMs for voice assistants and predictive maintenance, preprocessing text, audio, and telematics data, crafting prompt engineering strategies, and supporting model integration with cross-functional teams. Required qualifications include a Bachelor's or Master’s in Computer Science, Electrical Engineering, Data Science, AI, or related field; proficiency in Python; familiarity with PyTorch or TensorFlow; foundational knowledge of machine learning, NLP, and transformers; and exposure to generative AI frameworks such as OpenAI or Hugging Face. Preferred skills include experience with embedded systems, automotive software, voice recognition, multimodal AI, automotive communication protocols (CAN, LIN, Ethernet), cloud AI services (AWS SageMaker, Azure), and an understanding of functional safety and cybersecurity in automotive AI.