Lead ML Ops Engineer
Klaviyo
This job is no longer accepting applications
See open jobs at Klaviyo.See open jobs similar to "Lead ML Ops Engineer" Glynn Capital.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:
This Lead MLE is responsible for technical leadership on 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. The candidate should have at least 5 years of technical expertise in MLOps or adjacent areas. Please note that this role is based in Boston and requires a hybrid, onsite component.
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 successfully contributed multiple PRs to projects in flight. You have met with stakeholders such as Data Scientists 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. 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 and helping them improve their engineering quality. |
90 days | You will have developed at least two majors feature. You will be familiar with all of the team’s systems and have joined the team’s on-call rotation. You will be a leading voice on team discussions. You will have started to formulate a technical vision for priorities for the upcoming quarter of work. 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 and EM 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:
- Minimum 5 years experience in ML Ops
- Recent experience in MLOps that demonstrates technical leadership
- 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.
Nice to have:
- Experience with Jenkins, Ray, Spark, Kubeflow, MLFlow, Huggingface, GPU, Deep Learning
#LI-Onsite #LI-CB2
The starting 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.
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.
You can find our Job Applicant Privacy Notice here.
This job is no longer accepting applications
See open jobs at Klaviyo.See open jobs similar to "Lead ML Ops Engineer" Glynn Capital.