Trainee / Junior AI Engineer supporting real customer projects at WE BUILD AI. Working with AI applications including automation solutions and machine learning models in a hybrid environment.
TC
Hybrid Lead Artificial Intelligence Engineer – Customer Support Systems
Posted 2 months ago
About the role
- Lead AI Engineer focused on intelligent automation in Customer Support for Disney. Collaborate with teams to design and productionize AI-driven systems enhancing customer experiences.
Responsibilities
- Rapidly analyze and prototype AI-driven solutions that address key pain points for both customers using self-service systems and customer service (CS) agents interacting with internal tooling
- Own and maintain production AI systems, including those leveraging large language models (LLMs); this includes optimization, fine-tuning, and debugging to ensure robustness and performance at scale
- Bridge customer support needs with commerce platform capabilities, identifying which problems can be solved using existing infrastructure and which require new AI-powered solutions
- Assess the effectiveness of deployed AI solutions through a data-driven lens, continuously iterating on what works and sunsetting or replacing what doesn’t deliver meaningful impact
- Collaborate with other AI-focused teams across Disney Streaming, sharing innovations and adopting best practices to drive consistency, scalability, and impact in AI initiatives.
Requirements
- Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field; PhD is a plus
- 2+ years of hands-on experience building, deploying, and evaluating LLM based solutions
- Minimum 7 years of related work experience in building, deploying, and evaluating real-world machine learning solutions
- Proficiency in Python, SQL, and other relevant programming languages
- Experience with data wrangling and analysis tools such as Pandas, NumPy, and working knowledge of databases like MySQL and PostgreSQL
- Familiarity with big data and workflow platforms, including Spark, Databricks, Snowflake, Airflow, Jupyter, and GitHub
- Proven experience leading end-to-end ML project lifecycles, including model design, experimentation, product deployment, CI/CD for ML pipelines, and ongoing monitoring
- Excellent problem-solving abilities, with strong communication and collaboration skills.
Benefits
- A bonus and/or long-term incentive units may be provided as part of the compensation package
- Full range of medical benefits
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