Senior Machine Learning Ops Engineer

At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit careers.klaviyo.com to see how we empower creators to own their own destiny.

Why You Should Join Klaviyo!

At Klaviyo, we love tackling tough engineering problems and look for employees who are passionate about building, owning & scaling features end to end from scratch and breaking through any obstacle or technical challenge in their way. We push each other to move out of our comfort zone, learn new technologies, and work hard to ensure each day is better than the last. Learn more about our engineering culture at https://klaviyo.tech

 

Why You Should Join the Data Science Platform Team!

The Data Science Platform team empowers our data scientists to build scalable, reliable, advanced, and iterative machine learning systems that automate and streamline Klaviyo's operations, make Klaviyo's product more intelligent, and transform Klaviyo's future. We support teams building systems like fraud detection, content understanding, forecasting, experiment optimization, and a host of other algorithms. Our efforts are focused on end-to-end use cases from rapid exploratory analytics to model deployment. We develop systems for experiment tracking, analysis environments, distributed training, and high-availability online model serving. Our stack includes tools like Kubernetes, Jupyter, MLFLow, Airflow, Ray and Spark and we assist in deploying models touching nearly every part of Klaviyo’s business and product.

 

About the role:

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.

 

Please note that this role is based in Boston and requires a weekly hybrid, onsite component. 

 

How you'll have an impact:

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.

 

What we're looking for:

We encourage candidates to apply even if they do not meet all the qualifications listed below. ML Ops is a rapidly evolving space and we are all constantly learning!

• 4+ years industry experience in ML Ops or related spaces like data, infrastructure