Engineering Manager, ML Ops

Key Skills

AWS, Deep Learning, GPUs, HuggingFace, Jenkins, Kubeflow, Kubernetes-K8s, Machine learning techniques, Mentoring, MLflow, MLOps tools, People management, Python Programming, Ray.io, Software Development, Spark Core, Terraform

Job Description

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.

About the role:

The Engineering Manager of the Data Science (DS) Platform team is responsible for leading the team of Machine Learning 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.

Engineering Managers at Klaviyo are hands-on, meaning they spend some significant part of their time writing and reviewing code and specs, as well as working with counterparts such as data scientists using the frameworks developed by the Platform team and engineering teams who rely on the deployed models to power customer facing features. Your tech stack includes Python, AWS, Kubernetes, and Terraform. Please note that t his role is based in Boston and requires a hybrid, onsite component.

How you’ll have an impact:

30 days 

• You will have finished onboarding including engineering and data science specific onboarding, and your local developer environment is set up and usable.
• You will have met with all of the team members and have already contributed a first PR.

60 days 

• You will have successfully contributed multiple PRs to projects in flight.
• You regularly have 1:1s with team members (currently 3 engineers).
• You will have met with stakeholders such as Data Science Managers, Product Managers, Legal & Security, and Data Infrastructure engineers in order to gather the necessary context for future projects and understand requirements or constraints on system design imposed by those dependencies.

90 days

• You will have solidly taken over team processes and be actively planning team work both current and upcoming, and you’ve started to formulate a vision for priorities for the upcoming quarter of work.
• You will be well versed in existing systems, including what areas have gaps that need to be filled, and have started working with the team and stakeholders to scope and prioritize solutions.

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 will have developed short, medium, and long-term roadmaps in partnership with stakeholders that give confidence that the DS Platform services will be able to scale at the same pace as Klaviyo’s DS and ML business needs.
• You will have hired or are in the process of hiring additional engineers to grow the team.
• You will have formulated career development goals and plans for your team members and are mentoring them on how to succeed.

What we’re looking for:

• 2+ years people management experience
• 5+ years technical expertise in MLOps or adjacent areas
• Experience putting machine learning models with a variety of applications and usage patterns into production
• Proficient with Python, AWS, Terraform, Kubernetes
• Excited to read the code, understand the product area, and give applicable technical mentorship.
• Comfortable giving performance review, coaching team members on their technical growth, and mentoring team members at various levels

Nice to have:

• Experience with Jenkins, Ray, Spark, Kubeflow, MLFlow, Huggingface, GPU, Deep Learning