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Lead ML Ops Engineer

  • Boston, MA
  • Data Science

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 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 specialize in certain areas but 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

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:

The Lead ML Ops Engineer of the Data Science (DS) Platform team is responsible for technical leadership on the team of engineers who build and maintain the services that enable and accelerate Data Science and Machine Learning at Klaviyo, including tooling for training, testing, serving, and monitoring models. Klaviyo continues to invest heavily in machine learning and data science, and you have the opportunity to lay the foundation for work we do in these areas.

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 lead team member, you will be responsible for architecture and roadmap planning in coordination with the manager, product manager, and stakeholders. 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 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 lead and ship multiple feature contributions, and 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 formulating a technical roadmap, improving team processes, and collaborating with Product and stakeholder teams on design.
  • You will be a leading voice on team discussions.
  • You understand what areas have gaps that need to be filled and where there are opportunities to improve functionality, scalability, reliability, etc.

Up to 1 year 

  • You will have successfully led the team to deliver multiple high impact projects that significantly improve the functionality and scalability of systems owned by DS Platform. 
  • You work with the team, EM, and PM to develop and maintain short, medium, and long-term technical roadmaps.
  • The team’s engineering quality, and system stability and reliability have noticeably improved because of your guidance and technical leadership.

What we're looking for:

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

  • 8+ 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 stakeholders, especially with data scientists
  • Proven experience with being a coach/mentor for team members and helping them grow
  • Demonstrated technical leadership and experience developing and selling technical roadmaps


Nice to have:

  • Experience with large-scale data processing tools like Spark, Flink, Hive, Beam
  • Experience with CICD using tools like Jenkins
  • Experience with MLOps frameworks like Ray, Kserve, Kubeflow
  • Experience working with GPU workloads
  • Experience contributing to open source projects

#LI-Onsite     #LI-CB2

The pay range for this role is listed below. Sales roles are also eligible for variable compensation and hourly non-exempt roles are eligible for overtime in accordance with applicable law. This role is eligible for benefits, including: medical, dental and vision coverage, health savings accounts, flexible spending accounts, 401(k), flexible paid time off and company-paid holidays and a culture of learning that includes a learning allowance and access to a professional coaching service for all employees.

Base Pay Range For US Locations:
$192,000—$288,000 USD

Get to Know Klaviyo

We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us.

Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.

IMPORTANT NOTICE: Our company takes the security and privacy of job applicants very seriously. We will never ask for payment, bank details, or personal financial information as part of the application process. All our legitimate job postings can be found on our official career site. Please be cautious of job offers that come from non-company email addresses (, instant messaging platforms, or unsolicited calls. 

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