Senior ML Engineer at Shopmonkey
San Jose, California, USA -
Full Time


Start Date

Immediate

Expiry Date

13 Dec, 25

Salary

195000.0

Posted On

16 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

Shopmonkey’s vision is to help every shop thrive by equipping them with the tools they need to run and grow their business. Our cloud based all-in-one shop management software takes owners and technicians from quote to cashing out a satisfied customer. Our software has a modern and intuitive UI and our backend is powered by the latest technologies so our clients can focus on the things they do best.
As a Senior ML Engineer at Shopmonkey, you will be a part of a globally distributed engineering team working closely with your product and design counterparts. You will have the chance to work on the frontier of agentic AI, applying cutting-edge LLMs and co-pilot frameworks to meet real-world auto shop needs. Shopmonkey has the structured data, workflows, and operational maturity to deliver AI that’s not only intelligent but trusted and useful. You’ll move fast to bring AI agents from discovery all the way through production, helping to shape the future of the automotive care experience. Please note this is a hybrid position, with an expectation of 2-3 days per week on-site at our Morgan Hill office.

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.
  • Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards.
  • 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.
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