Daloopa Engineer

Responsibilities:

• Lead and transform: build and scale the supervised learning platform that turns analyst corrections into training data. The connective tissue between our human-in-the-loop process and our models.
• Design and operate the extraction pipelines that turn PDFs and HTML filings into structured, audit-ready data, in partnership with the ML team.
• Build the routing and uncertainty-aware systems that decide when a model can act alone and when an analyst needs to weigh in.
• Integrate LLMs and ML models into production via API endpoints and inference pipelines, with the reliability and observability our clients require.
• Define database schemas and architectural decisions for performance, scalability, and resilience across a domain that spans every public market and accounting convention.
• Champion clean, maintainable code through reviews, tests, and clear documentation.

Requirements:

• 4+ years of professional backend engineering experience.
• Strong expertise in Python and Django (or equivalent backend frameworks).
• Hands-on experience integrating ML models or LLMs into production: model serving, inference APIs, vector stores.
• Deep understanding of relational and non-relational databases (PostgreSQL, MySQL, Redis, DynamoDB).
• Experience with distributed systems, caching, and asynchronous task queues (Celery or equivalent).
• Track record of leading backend or ML-integrated projects end-to-end.
• Genuine interest in the problem domain.
• Financial data, supervised learning systems, or human-in-the-loop AI.
• You should be the kind of person who reads the AlphaSense product launches and has opinions.