Lead AI/ML & MLOps Engineer executing projects from data foundations to model deployment. Collaborating with sales to drive AI/ML engagements for our clients.
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
Requirements
- 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
Benefits
- Offers Equity
- Offers Bonus
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