• 4+ years industry experience in ML Ops or related spaces like data, infrastructure or platform engineering
• Hands-on experience in shipping, monitoring, and debugging machine learning-based projects in production
• Strong software engineering and cloud infrastructure skills with code fluency in Python (we use Python, Terraform and Kubernetes on AWS)
• An excellent communicator and able to collaborate on complex issues with a variety of stakeholders, especially with data scientists
• Proven experience with being a coach/mentor for team members and helping them grow

Desirable

• As a Senior Machine Learning Engineer, you will be a key contributor to the DS Platform team’s efforts to build and improve the tools, systems, and software services that data scientists depend on to create cutting edge models that power Klaviyo’s most advanced features
• You will be responsible for developing tools to train and develop models, serve models in production, and monitor models’ long term performance
• You’ll work with a modern software stack built on Kubernetes, Sagemaker, MLFLow, Spark and Ray, helping to support models running on technologies such as PyTorch, ScikitLearn, Huggingface and more
• As a senior team member you will help to level up our software engineering, dev ops, and DS/ML skills in a collaborative hybrid environment surrounded by engineers and data scientists passionate about producing high quality and high value models
• 30 days:
• You spend the first two weeks in Klaviyo boot camp learning about the company and using the product
• Your onboarding buddy and the team help you get contributing your first PR!
• You are participating in team meetings and processes and meeting key stakeholders from Data Science & Engineering teams
• 60 days:
• You own and ship your first feature contribution!
• You develop a career plan and personal goals with your manager
• You have a firm understanding of at least one of the systems that the team owns and are consistently contributing code
• You are actively reviewing teammates’ code and helping them improve their engineering quality
• You understand the team’s vision and roadmap
• 90 days:
• You own and ship multiple feature contributions. You are shipping code independently
• You are familiar with all of the team’s systems and have joined the team’s on-call rotation
• You are actively reviewing teammates’ work and beginning to mentor other team members
• You are contributing to roadmap planning, improving team processes and collaborating with Product and stakeholder teams on design
• Up to 1 year:
• You successfully lead multiple high impact projects that significantly improve the functionality and scalability of systems owned by Data Science Platform
• You provide mentorship and help the team improve engineering quality, system stability, and reliability