Job Description
📋 Description Own end-to-end ML lifecycle from opportunities to deployment. Design/deploy/monitor ML models in production. Build ML for multi-modal data (CV, NLP, graphs). Architect scalable multi-tenant inference across geographies/clouds. Move models from concept to production; monitor drift and fairness. Collaborate with engineers, product managers, designers, and domain experts. 🎯 Requirements Python and SQL for complex analysis. Production ML lifecycle: design, deployment, monitoring. Explain ML concepts to non-technical stakeholders. Deep CV or LLM expertise; architecture decisions. ETL/ELT with dbt and Snowflake. Cloud (Azure/GCP) + Docker; Git/GitHub; CI/CD. 🎁 Benefits Employee share scheme: own part of Auror. Flexible, outcomes-focused culture. Shorter work weeks: Friday afternoons off. Wellness Days and up to $500 for expert sessions yearly. Health care plan: Medical, Dental & Vision; 100% for you. Family-friendly: 12 weeks parental leave; 6 weeks for non-birth.
