Help build the intelligence layer
Elcast.ai is looking for senior technical contributors who can work across modelling, architecture, feature engineering, data pipelines, market reasoning, and production-quality code.
This is not a notebook-only data-science role. A successful candidate will be comfortable contributing across both code and system design.
Work on the problems that move the market.
Our work sits at the intersection of machine learning, market structure, and production-grade engineering. You'll contribute across the full stack.
CatBoost ranking and ML evaluation
Build and evaluate learning-to-rank models with rigorous offline and backtest protocols.
Time-aware experiment windows
Design and analyze experiments with proper temporal splits and forward-chaining validation.
Pydantic-driven Python architecture
Write robust, typed, and validated code with Pydantic models and clear domain boundaries.
Modular registries and system design
Work with registries and plug-in style components for extensibility and maintainability.
PostgreSQL analytical pipelines
Build analytical pipelines using SQL functions, views, and materialized views for performance and clarity.
Parquet caching and reproducible workflows
Leverage columnar caching and deterministic data workflows for speed, reliability, and reproducibility.
Repo-wide refactoring and documentation
Improve code quality across the stack with refactoring, testing, and clear, up-to-date documentation.
Market-data feature engineering
Engineer high-signal features from market data while preventing look-ahead bias and information leakage.
Get in touch.
Investor inquiries, technical hiring, data partnerships, and questions about the platform.