Principal Machine Learning Engineer, Lime

• 8+ years of professional experience in software engineering or applied ML, with a record of delivering production level systems
• 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
• If you want to make an impact, Lime is the place for you. Not sure if you meet all the qualifications? If this role excites you we encourage you to apply. Explore all opportunities on our career page

Desirable

• Lime is hiring a Principal Machine Learning Engineer to join the Data Science & Analytics team and build our Machine Learning Center of Excellence
• In this role, you will be a senior individual contributor reporting to the Head of Data and partnering with senior software engineering leadership across Lime’s technology teams
• This role will be responsible for shaping how machine learning is built, deployed, and operated across Lime
• You will set technical direction and standards for ML infrastructure, featured development, and model lifecycle management
• This role blends deep hands-on work with significant cross-team leadership and influence
• 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