Sr. AI/ML Engineer (LLM)

Job description

Company Description

Dealer Automation Technologies is a leading Information Technology Services company that provides Software as a Service (SaaS) solutions for the automotive industry. The company specializes in Process Automation, Advanced Analytics, and Augmented Intelligence to redefine dealership operations. With a focus on intuitive user experiences and cutting-edge technologies, Dealer Automation Technologies is paving the way for innovation in the sector. Combining the agility of a startup with the expertise and business acumen of seasoned leaders, the company operates without dependence on legacy systems, fostering a dynamic and innovative work culture.

Role Description

This is a full-time, on-site role located in Miami, FL, for a Senior AI/ML Engineer specializing in Large Language Models (LLMs) to join our team. You will play a key role in designing and implementing workflows that leverage large language models (LLMs, LAMs, LMMs, LVLMs, etc.) to automate processes and drive innovation in our products. The ideal candidate will have a deep understanding of NLP, experience with foundational models, and a flexible, problem-solving mindset. You will collaborate closely with cross-functional teams, contributing to the development of scalable AI driven solutions. Other primary responsibilities include designing and implementing machine learning models, particularly in natural language processing and large language models, building scalable algorithms, conducting research on neural networks, and evaluating model performance. Additionally, the engineer will collaborate with cross-functional teams to ensure seamless integration of AI/ML components into the company’s software offerings.

Major Areas of Responsibility

• Design, Implement, and optimize workflows that incorporate large language models to automate and enhance product features.
• Leverage existing foundational models and adapt them to fit into various product requirements, ensuring alignment with business goals.
• Collaborate with product managers, data scientist, and software engineers to integrate LLM-based automation into scalable solutions.
• Create and architect interpreters, Agented Systems, and integrate multi-hop RAG and other LLM experiences into existing systems to coordinate knowledge responses.
• Research and evaluate new technologies and methodologies in the LLM space to continuously improve product automation.
• Work on the customization and fine-tunning of models to optimize performance for specific use cases.
• Develop, test, and deploy LLM-based services in production environments.
• Provide AI/ML technical leadership and mentorship to other engineers on the team.
• Ensure that LLM integrations are efficient, scalable, and secure, adhering to industry best practices.