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 ML modeling, data pipelines, MLOps, and agentic AI systems to meet real-world auto shop needs. Shopmonkey has the structured data, workflows, and operational maturity to deliver ML powered systems that are not only intelligent but trusted and useful. You’ll move fast to bring ML systems from discovery all the way through production, helping to shape the future of the automotive care experience. For any Bay area based candidates, this would be hybrid with 2-3 days/week office at our Morgan Hill, CA office for collaboration. 

What you will do:

• Design, build, and ship production-ready ML models across a range of problem spaces: regression, classification, clustering, ranking, and recommendation systems.
• Conduct end-to-end development of ML systems: data gathering, experimentation, feature engineering, model training, evaluation, deployment, and monitoring.
• Define and track model performance metrics, run A/B tests, and iterate based on real-world feedback.
• Help design and implement shared feature stores so that reusable features can serve multiple models consistently in both batch and real-time contexts.
• Work within a modern MLOps environment to ensure scalable and reliable deployment of models.
• Contribute to training infrastructure, model versioning, and CI/CD pipelines for ML workflows.
• Work closely with data scientists and data engineers to develop data driven solutions that are high impact for businesses.
• 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.
• Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization.
• Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards.
• Help build and ship AI agents that help automate key auto-shop business processes.

We are looking for people who have:

• Minimum of 5+ years of industry experience in applied machine learning; advanced degrees (Master’s or PhD) may offset years of experience.
• Proven experience shipping models into production (not just proof-of-concepts or notebooks).
• Proficiency in Python; experience with ML frameworks like PyTorch or Tensorflow.
• Strong foundations in classical ML/DL. Including some of the following: regression, classification, clustering, ranking, feature engineering, model evaluation, and experimentation.
• Bachelor’s degree in a STEM field, or equivalent practical experience.
• Strong collaboration and communication skills—comfortable working with PMs, designers, engineers and other cross functional team members.

Nice to have:

Candidates should have some experience in one or more of the following areas.

• Understanding of MLOps principles: model versioning, orchestration, evaluation, monitoring, model serving, and CI/CD for ML. 
• Understanding of MLOps, and experience with modern tooling like MLFlow, DVC, Airflow, etc.
• Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain).
• Experience with/interest in LLM workflows and agentic workflows
• Cloud infrastructure experience, (e.g. GCP, AWS).
• Familiarity with vector databases (e.g. Pinecone, pgvector) and embedding-based retrieval or similarity search.
• Strong SQL skills for working with large-scale data.
• Experience designing or contributing to feature stores (e.g. Feast, VertexAI Feature Store, Tecton) for shared, reusable feature pipelines.

Bonus Points:

• 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.

In the United States, the range is typically a salary of $165,000 to $200,000 + bonus + equity + benefits. The range provided is Shopmonkey’s reasonable estimate of the base compensation for this role. The actual amount will be based on job-related and non-discriminatory factors such as location, experience, training, skills, and abilities. Consult with your Recruiter during the initial call to determine a more targeted range based on these job-related factors. In addition to this base compensation company stock options and benefits as outlined below are included.

We're looking for an Engineering Manager I to lead one of our autonomous feature squads. You'll own the day-to-day engineering leadership of a cross-functional team (1 PM, 1 Designer, 4–5 engineers) responsible for a meaningful area of the Shopmonkey platform. This is not a "project manager with an engineering title" role. You are technical, you are in the code, and you care deeply about how software gets built — not just that it ships. You won't be on the critical path for planned project work, but you'll be deeply involved in guiding your team through every phase of the SDLC: scoping, design, implementation, testing, release, and iteration. Your job is to make your team faster, sharper, and more effective — by coaching, unblocking, and identifying the gaps nobody else sees. You'll also contribute directly to the codebase. Not as a primary feature developer, but as a force multiplier — proactively improving code quality, tackling the work that falls between the cracks, and leading by example when it matters.

Our platform is built on two primary monorepos (backend and frontend) using TypeScript throughout. The stack includes React, Node.js, Next.js, Redux, and Redis on the application side; CockroachDB and ClickHouse for data; Synadia NATS for messaging; and GCP for infrastructure. We use OpenTelemetry and Prometheus for observability, with supporting services in TypeScript and Go. We don't expect expertise across all of these — we're looking for strong fundamentals and the ability to learn quickly.

What you will do:

• Lead a feature squad end-to-end: people, process, and technical direction.
• Own performance management for your engineers — regular 1:1s, growth conversations, honest feedback, and formal reviews.
• Partner closely with your PM and Designer to shape quarterly project plans that balance customer value, technical health, and business impact.
• Guide your team through the full SDLC — you should be competent and opinionated at every stage, from system design through production observability.
• Contribute to the codebase as a technical force multiplier: filling gaps, improving quality, and modeling engineering standards.
• Operate within our quarterly planning and 2-week cycle cadence, helping your squad maintain focus and predictability.
• Build and maintain a healthy remote-first team culture — clear communication, strong async habits, and flexibility balanced against team needs.
• Participate in hiring — sourcing, interviewing, and closing engineering talent for your squad and the broader org.

We are looking for people who have:

• 2+ years of formal engineering management experience, leading a team of software engineers through shipping production software.
• A strong technical foundation — you've built and operated production systems and can earn credibility with senior ICs through your technical judgment.
• Proven ability to coach and develop engineers across multiple levels.
• High emotional intelligence and communication skills. You navigate ambiguity, give hard feedback with care, and build trust quickly — especially important in a remote environment.
• Sound business judgment — you understand why the team is building what it's building, and you push back when priorities don't make sense.
• Experience working in cross-functional product teams (PM, Design, Engineering).
• Comfort with remote-first work across time zones. You value flexibility but put team needs first.

In the United States, the range is typically a salary of $145,000 to $180,000 + bonus + equity + benefits. The range provided is Shopmonkey’s reasonable estimate of the base compensation for this role. The actual amount will be based on job-related and non-discriminatory factors such as location, experience, training, skills, and abilities. Consult with your Recruiter during the initial call to determine a more targeted range based on these job-related factors. In addition to this base compensation company stock options and benefits as outlined below are included.