About the role

Principal Machine Learning Engineer at Lime driving ML strategy and team collaboration on machine learning infrastructure and processes.

Responsibilities

Drive alignment across teams on ML strategy, standards, and long-term technical direction by serving as a technical leader for Lime’s ML Center of Excellence
Guide recommendations for ML infrastructure, tooling, and architecture (training, serving, feature stores, experimentation, monitoring)
Define and evolve ML development processes, including model review, experimentation rigor, deployment, optimization, and operations
Establish best practices for ML monitoring, observability, alerting, and model performance health in production
Drive reusable feature development patterns and shared ML capabilities that enable teams to move faster and more safely
Partner with platform, data, and product engineering teams to ensure ML systems are reliable, scalable, and cost effective
Identify and prioritize opportunities where ML will improve Lime’s product, operations, or efficiency
Act as a force multiplier by mentoring data scientists and machine learning engineers, raising the quality bar for machine learning across Lime

8+ years of professional experience in software engineering or applied ML
Fluency in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow) and data tools (e.g. SQL, pandas, spark, airflow)
Strong foundation in ML fundamentals, including model evaluation, experimentation, optimization, production deployment, and operations
Strong system design skills and comfort working with distributed systems
Track record of influencing ML architecture and practices across multiple teams
Background in domains relevant to Lime (e.g., forecasting, optimization, pricing, marketplace dynamics)
Prior experience building a ML platform or center of excellence through defining ML standards, governance, or shared tooling at scale