CookUnity is looking to design, build, and productionize personalization and recommendation systems to help customers discover meals they'll love, ultimately expanding beyond delivery to become an innovating marketplace focused on 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 (with bonuses for experience in Snowflake, PyTorch, Airflow, MLFlow, ECS)
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.
- A proven ability to work across disciplines and guide stakeholders—while also owning the technical end-to-end performance of your models.
- 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
