Applied AI Researcher

About Brandlight

Brandlight is the leading enterprise AI visibility platform, built to help the world’s leading brands understand, manage, and optimize how they appear across AI-driven search, commerce, and advertising.

As AI rapidly becomes a trillion-dollar marketing and distribution channel, Brandlight is defining the systems that decide what brands are surfaced, trusted, and chosen.

Join our team and help build the next generation of tools shaping the future of brand management in an AI-first world.

About The Role

This is a unique role at the intersection of classic machine learning, deep learning and state of the art LLMs and agentic workflows.

As an Applied AI Researcher at Brandlight, you’ll work at the frontier of how large language models are transforming marketing in the age of AI. You will design and develop novel methods to measure, analyze, and influence how LLMs perceive and represent brands, from brand visibility, content optimization and creation, ads and agentic commerce.

Responsibilities

• Design and build core algorithms and LLM pipelines for tasks like sentiment analysis, bias detection, content generation, agentic commerce, etc.
• Design and build comprehensive benchmarks (synthetic, adversarial, real-world) and conduct experiments, evaluating their effects when deployed in real-world systems.
• Prototype new models and systems, collaborate with engineering teams to integrate research outputs and deploy scalable, production-grade systems.
• Drive internal and external knowledge sharing: write research reports, blog posts, white papers, or conferences to position Brandlight as a thought leader in generative AI.
• Stay up to date with the state of the art in NLP, LLMs, generative models, agentic AI and new emerging tools and algorithms.
  
  

• B.Sc degree in Computer Science, Information Systems or related field.
• 6+ years of hands-on industry experience as data or backend engineer.
• Excellent SW engineering skills, proficient python developer.
• Excellent SQL skills, including query optimization.
• Experience with big data frameworks.
• Experience with BigQuery & Airflow a big advantage.
• Experience working with LLMs, Vector DBs and ML knowledge a big advantage.
• Ability and desire to work in a fast paced, demanding and sometimes ambiguous environment.