Senior Machine Learning Engineer

Pennylane SAS

12h•Remote

About The Position

This role is pivotal in helping Pennylane meet its high delivery standards by bringing engineering and machine learning expertise to large projects. The data team's mission is to treat data as a production asset, making it available company-wide and using it proactively to improve Pennylane’s user experience. Every decision not backed by data is likely to be challenged, a culture embraced by leadership and promoted throughout the company.

Requirements

Python
PySpark
Redshift
Airflow
AWS Sagemaker

Responsibilities

Design machine learning solutions and tools across the entire ML lifecycle, from model training and tuning to deployment, inference, experimentation, and monitoring.
Contribute to all parts of the Data Platform, from data ingestion and validation to transport, storage, and exposure to consumers, to feed machine learning applications in production.
Work closely with fellow Machine Learning Engineers and Data Engineers to improve the ML ecosystem and enable a variety of ML applications.
Collaborate with Product teams to explore new possibilities and ensure user needs are at the center of all initiatives.
Proactively contribute to the team’s roadmap.
Work with engineers and data practitioners on improving the stack and data platform.
Share learnings and best practices within the team.
Recruit and mentor new team members.
Take on increased accountability in project leadership.
Design and implement new processes, tools, and best practices to enhance team efficiency.