Senior ML Engineer at Shopmonkey building production-ready ML models and managing end-to-end ML system development. Collaborating with cross-functional teams to drive high-impact business solutions.
Responsibilities
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.
Requirements
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.
Benefits
Medical, dental, vision, and life insurance benefits available the 1st of the month following hire date
Short term and long term disability
Employee assistance program
Reimbursement for a personal health and wellness membership
Generous parental leave
401(k) available upon hire
11 paid holidays
Flexible time off - take the time off you need!
Matching donations for approved charitable organizations
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