ML Ops Engineer

Key Skills

AWS, GoLang, HuggingFace, Keras software library, Kubernetes-K8s, Linux Operating system, Machine learning techniques, MLOps tools, Python Programming, PyTorch, Ray.io, Spark Core, TensorFlow, Terraform, Unix Operating system

Job Description

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.

About the team:

Klaviyo operates a real-time data analytics platform coded primarily in Python that is built for massive scale and hosted on Amazon Web Services (AWS). Engineers come to Klaviyo with experience in a variety of languages and from a number of disciplines.

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 https://klaviyo.tech

About the role:

As a Machine Learning Engineer II, 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, and Ray, helping to support models running on technologies such as PyTorch, SKLearn, Huggingface, and more.

You will learn from senior team members and level up your 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 and features.

How you'll have an impact:

30 days 

• You will have set up your local environment and contributed your first PR.
• You will be participating in team meetings and processes, and have met several members of the wider Data Science team.

60 days 

• You will have a firm understanding of at least one of the systems the team owns, and will be actively and consistently contributing code on a regular cadence.
• You will be actively reviewing teammates’ code.

90 days

• You will have developed at least one major feature.
• You will be familiar with all of the team’s systems and have joined the team’s on-call rotation, demonstrating ownership and mastery.
• You will be an active contributor to team discussions on technical decisions.

Up to 1 year 

• You will be a key member of the team’s technical and social fabric, shipping impactful code and systems, responding to incidents, monitoring and ensuring uptime, and collaborating with teammates effectively to solve problems.

What we're looking for:

• Prior industry experience as software engineer or machine learning engineer
• Python
• AWS
• Unix/Linux
• Networking

Nice to have:

• Kubernetes
• Terraform
• Go
• Sagemaker
• ML frameworks such as Huggingface, PyTorch, Tensorflow, Keras
• Distributed training frameworks such as Spark, Ray, etc

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.

Upon request, you can receive additional information about the compensation and benefits for this role. Requests can be submitted here . Additional information regarding benefits can be found at klaviyorewards.com .

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.