Develop new models end-to-end, from understanding product requirements to implementation and deployment.
Align with various stakeholders, including Product Managers, Data Engineers, and Backend Engineers to ensure seamless integration of ML solutions into the product ecosystem.
Develop models: design, train, evaluate, and iterate on ML models using modern techniques tailored to real business problems.
Put models into production with robust technical implementation and quality assurance processes.
Create an ML Ops framework for the team to ensure our models scale effectively with proper monitoring and alerts (e.g., model drift detection, performance tracking, automated retraining pipelines).
Share best practices within the ML team, contributing to internal knowledge, tooling improvements, and mentoring peers.

3+ years of experience ML Engineer coupled with ML Ops, particularly in developing client-facing products.
Experience building and optimizing machine learning models for external clients.
Proficient at writing resilient, high-quality, testable code in Python
Understanding of FastAPI or a similar web framework.
Proven track record of identifying complex problems and implementing effective solutions in machine learning contexts.
Proactivity to improve processes
Fluency in English

Senior Machine Learning Engineer – AI Product

Key skills