Klaviyo
Senior Machine Learning Engineer, ML Research
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:
The Senior Machine Learning Engineer will help build foundational models at Klaviyo that extract insights from the massive streams of data that Klaviyo ingests continuously. You will work with teammates including data scientists to apply cutting edge techniques from deep learning, language modeling, recommender systems, and more to generate value for our customers by allowing them to target and personalize their messages. You have capable software engineering skills and are familiar with the entire model lifecycle from inception to production.
You use and promote best practices to ensure high software code quality and machine learning performance. You have experience in machine learning, and have already trained and developed models in the recommender, NLP, or related areas working. You are determined, motivated, and ready to overcome new challenges to build the best solutions.
This role is based in Boston, MA and requires a weekly hybrid in-office component.
How you’ll have an impact:
30 days
- You will have finished on-boarding including engineering and data science specific on-boarding.
- Your local developer environment is set up and usable.
- You will have met multiple members of the Data Science team and are starting to familiarize yourself with both the Klaviyo product and the data sources available to you.
60 days
- You will understand what’s needed to tackle your initial project including the data needed, the success metrics, the technical approach, the experiments needed to test performance in production, etc.
- You are able to pull data and train and test models in Klaviyo’s dev environment.
- You are actively contributing PRs and code reviews to teammates.
90 days
- You will be actively iterating on models for your first project.
- You will be actively working with teammates across Data Science to accelerate progress.
- In partnership with your manager, you will be regularly in conversation with Product and Engineering stakeholders to make sure work remains aligned with company priorities.
Up to 1 year
- You will have developed multiple impactful models that use Klaviyo’s data, which have been put into production and are generating value in novel and powerful ways for our customers.
- You are regarded as an expert in your area and help to support and teach others to work with and build upon the models and systems you’ve developed.
What we’re looking for:
- 5+ years experience in machine learning or data science
- Experience in at least one of NLP or recommender systems.
- Experience putting models into production, monitored and maintained them in production
- Experience writing code to high software engineering standards, following best practices such as test-driven development, code review
- Experience working with databases, REST interfaces, and other modern SaaS development patterns
Nice to have:
- Personally put models into production, monitored and maintained them in production
- Experience with frameworks such as Huggingface, PyTorch, Tensorflow, Keras
- Experience with distributed training with Spark, Ray, etc.
- Experience working with customers directly
#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:$156,800—$235,200 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.
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