CookUnity is looking to design, build, and productionize personalization and recommendation systems to help customers discover meals they'll love, ultimately empowering chefs to nourish the world.
Requirements
- Deep experience building recommendation engines, personalization pipelines, ranking/relevance models, search optimization, or embedding-based features.
- Hands-on familiarity with A/B testing frameworks, and skills in experimentation design, causal inference, and measuring incremental impact.
- Strong programming chops in Python and SQL
- experience in Snowflake, PyTorch, Airflow, MLFlow, ECS
- A proven ability to work across disciplines and guide stakeholders—while also owning the technical end-to-end performance of your models.
Responsibilities
- Architect and deliver production-grade recommendation and personalization systems, from user modeling to ranking algorithms and embeddings.
- Quantify and optimize business impact through A/B testing, experimentation design, causal inference, and lift analyses.
- Translate product and business needs into effective, data-driven solutions that scale.
- Collaborate with cross-functional teams to embed experimentation and feedback loops into our workflows.
- Mentor and coach the data team on best practices in ML model validation, experimentation, and scalability.
Other
- 6+ years in data science, machine learning, or applied statistics.
- Bonus if you’ve worked in marketplaces, subscription services, food-tech, or adjacent domains.
- Unlimited PTO
- 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical
- A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly
