Related skills
snowflake sql python databricks dbt📋 Description
- Translate business problems into production AI systems across investment/workflows.
- Build and maintain data pipelines, feature stores, and retrieval layers.
- Develop, evaluate, and iterate on LLM-based apps, agents, and ML models in production.
- Own data quality, lineage, and observability for AI workloads.
- Deliver end-to-end AI use cases from scoping to shipping.
- Collaborate with Applied AI and Tech Strategy teams globally.
🎯 Requirements
- 6+ years in data engineering and applied ML/AI with production systems.
- Strong Python, SQL, and modern data stack (Airflow, Dagster, dbt, Spark, Snowflake/Databricks).
- Hands-on LLMs experience: RAG, fine-tuning, evaluations, and agentic workflows.
- Able to turn vague business questions into shipped products.
- High signal-to-noise thinking; drive delivery with incomplete data.
- Exceptional communication with technical and non-technical stakeholders.
🎁 Benefits
- Flexible work arrangement: 4 days in office, 1 day flexible.
- Reasonable accommodations for applicants/employees with disabilities.
- Equal opportunity employer; inclusive, diverse workforce.
Meet JobCopilot: Your Personal AI Job Hunter
Automatically Apply to Engineering Jobs. Just set your
preferences and Job Copilot will do the rest — finding, filtering, and applying while you focus on what matters.
Help us maintain the quality of jobs posted on Empllo!
Is this position not a remote job?
Let us know!