Shopmonkey aims to help every shop thrive by equipping them with the tools they need to run and grow their business. This role will leverage AI and LLMs to automate key workflows and enhance the customer experience within the automotive care industry.
Requirements
- Proven experience shipping models into production (not just proof-of-concepts).
- Proficiency in Python or TypeScript; strong SQL skills for working with large-scale data.
- Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain).
- Cloud infrastructure experience, (e.g. GCP, AWS).
- Understanding of MLOps, including orchestration tools like Airflow or Dagster.
- Conducted code reviews and have to ability to provide constructive feedback
- Prior experience working at a high growth startup.
Responsibilities
- Build and ship production-ready AI agents that automate key workflows (e.g., appointment setting, inventory ordering).
- Design and implement workflows and scripts for agentic conversations based on real-world data.
- Perform discovery with your Squad on key customer use cases and guide the development of use-case-driven agents.
- Conduct end-to-end development including data gathering, hypothesis testing, prototyping, demoing, productionizing, and monitoring.
- Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization.
- Design evaluation agents to enhance the quality and coherence of autonomous conversations.
- Work within a modern MLOps environment to ensure scalable and reliable deployment of models.
Other
- This is a hybrid role with in-office expectations 2-3 days/week at our Morgan Hill, CA office to collaborate and stay connected.
- Strong collaboration and communication skills—comfortable working with PMs, designers, engineers and other cross functional team members.
- Translate complex ML workflows into digestible updates for cross-functional stakeholders.
- Contribute to backlog velocity by owning appropriate tickets and delivering high-impact work in a collaborative, fast-paced environment.
- 5+ years of industry experience in applied machine learning or AI engineering; advanced degrees (Master’s or PhD) may offset years of experience.
