Lead and mentor the team, fostering skill development and best practices.
Guide the creation of SPECs and ensure clear documentation.
Act as the main point of contact for stakeholders, ensuring alignment between technical and business goals.
Develop and optimize data and ML solutions, integrating best practices for scalability and monitoring.
Oversee the full lifecycle of data pipelines and models—from EDA and feature engineering to deployment and continuous improvement.
Build Proof of Concepts (POCs) to validate and refine solutions.
Optimize performance, latency, memory, and throughput across data systems.
Design and maintain feature stores and data pipelines to support workflows.
Research and implement emerging technologies to enhance solutions.
Participate in candidate interviews and evaluations to help Mutt grow.

Experience leading and mentoring teams in Data projects, guiding technical decisions, and fostering team growth.
Proven ability to collaborate with stakeholders, translate business needs into technical solutions, and align priorities across teams.
Experience implementing ML-based systems, including model lifecycle management, monitoring, and MLOps pipeline setup.
Strong proficiency in Python (Pandas, Numpy, Jupyter, Scikit-Learn, XGBoost, Plotly).
Knowledge of SQL.
Experience with cloud platforms (AWS, GCP, Azure).

Lead Machine Learning Engineer

Key skills