Role overview
We are looking for a Machine Learning Engineer to join our AI team and help build and scale production-grade machine learning systems.
You will work on real-world ML problems involving large-scale behavioral and transactional data, contributing to models and pipelines that drive automated decision-making.
This role is highly hands-on and focuses on turning data into reliable AI systems — from engineering and experimentation to production pipelines.
You will work closely with the Head of AI in a small, highly technical team.
What we're looking for
- Build and maintain machine learning pipelines running on Databricks
- Design and implement feature engineering pipelines on large-scale datasets
- Develop and improve predictive models for customer and product behavior
- Support experimentation, evaluation, and model performance monitoring
- Contribute to data processing and ML infrastructure
- Collaborate on integrating ML and LLM-based components into production workflows
- Maintain clean, reliable code using **GitHub-based development workflows
Tech Stack**
- Machine learning frameworks (scikit-learn, LightGBM, PyTorch, etc.)
- Emerging LLM tooling and embeddings
- Python
- Spark / SQL
- Databricks
- *GitHub
- 1–3 years of experience in machine learning, data science, or ML engineering
- Strong Python programming skills
- Experience working with data pipelines or large datasets
- Familiarity with ML model development and evaluation
- Experience using Git-based workflows
- Comfortable working in a **fast-moving startup environment
- Experience with Databricks or Spark
- Experience with recommendation or prediction systems
- Exposure to LLMs and foundational models
- Experience deploying **ML pipelines in production
What We Offer**
- Work on real production AI systems
- A small and highly technical AI team
- High ownership and fast iteration cycles
- Opportunity to shape the **next generation of AI-driven systems
Tags & focus areas
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