About Us :

We are an AI-first career and hiring platform building the behavioral intelligence infrastructure for the future of hiring. Our mission is to create an intelligent system that understands candidates beyond resumes and helps organizations make better hiring decisions.

The Role :

You will build the first version of our Hiring Intelligence models - the system that transforms recorded interview transcripts into evidence-backed candidate profiles and explainable, ranked shortlists. This is an applied ML role, not a research role.

What You'll Do :

- Build an LLM-based structured extraction system that identifies competency evidence from interview transcripts.

- Develop a transparent scoring model that ranks candidates against role requirements.

- Create the evaluation infrastructure that tells us whether our models actually work.

- Design and run the human-labeling loop that powers model improvement.

- Own the full ML lifecycle : Prototype, Evaluate, Deploy, Monitor, and Improve.

Tech Stack :

Python, Postgres, S3, Docker, SQL, PyTorch, scikit-learn, Hugging Face.

Requirements :

- 4 - 7 years of hands-on experience building, shipping, and maintaining ML/AI products in production.

- Experience building LLM-powered structured extraction or pipeline systems.

- Strong classical ML fundamentals (Linear models, Gradient-boosted models, Regularization).

- Strong evaluation literacy (Precision@K, AUC, Calibration).

- Strong Python skills and experience with modern ML ecosystem.

- Comfortable with data and production infrastructure (SQL, Batch pipelines, Docker).