Senior ML Engineer

Shopmonkey•Austin, TX

54d•$163,000 - $195,000•Hybrid

About The Position

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 for San Francisco Bay area-based candidates, this is a hybrid role with in-office expectations 2-3 days/week at our Morgan Hill, CA office to collaborate and stay connected.

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.
Strong collaboration and communication skills-comfortable working with PMs, designers, engineers and other cross functional team members.
Conducted code reviews and have to ability to provide constructive feedback
Bachelor's degree in a STEM field, or equivalent practical experience.
5+ years of industry experience in applied machine learning or AI engineering; advanced degrees (Master's or PhD) may offset years of experience.

Nice To Haves

Prior experience working at a high growth startup.
Experience building consumer-facing agents in vertical SaaS, in the automotive industry (business or consumers).
Background in data processing or real-time analytics.
Experience with Snowflake or other large-scale data warehouse solutions.

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.