Role overview
- Full Time, Exempt
- Medical, Dental, Vision, Life, Short-Term & Long-Term Disability Insurance + FSA, HSA, and more
- 401k Employer Match after meeting eligibility requirements
- 14 Paid Holidays
- Unlimited PTO
- Paid Parental Leave
What you'll work on
- ML Engineering Expertise: 3+ years of experience building and deploying machine learning systems in production environments
- Python & ML Frameworks: Strong Python skills with experience in PyTorch, TensorFlow, scikit-learn, or similar ML frameworks
- Model Deployment: Experience deploying ML models to production, including MLOps practices, model versioning, and A/B testing
- Data Pipeline Experience: Strong background building data processing pipelines for training and inference
- Cloud ML Platforms: Experience with AWS SageMaker, GCP AI Platform, Azure ML, or similar cloud ML services
- Product Engineering Mindset: Understanding that technology exists to solve customer problems and create business value
- Problem-Solving Approach: You start with understanding the problem deeply before jumping to solutions
- Experimentation Mindset: You value learning through rapid experimentation and embrace a "progress over perfection" approach
- Outcome Orientation: You measure success by business impact and customer satisfaction, not just by model accuracy metrics
- Communication Skills: Ability to explain ML capabilities and limitations to both technical and non-technical stakeholders
- Agency Experience: Experience working effectively with development agency partners is a plus
- Domain Experience: Background in pricing systems, recommendation engines, or transactional platforms is highly valuable
What we're looking for
- Occasional travel may be required
Tags & focus areas
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