Lead Machine Learning Engineer
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 Lead 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 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.
The Lead MLE will be a technical leader within the organization, helping to set the standard for excellence, and will amplify their own impact by mentoring other team members on technical skills. You should have in depth experience in machine learning or data science, and have already trained and developed multiple advanced models in the recommender, NLP, or related areas.
How you'll have an impact:
Up to 1 year
What we’re looking for:
- 7+ years experience in machine learning or data science
- Must have led the development of complex models on massive data sets that power customer-facing features.
- Ability to develop technical roadmaps for solving complex business problems using ML
- Experience in at least one of NLP or recommender systems
- Experience working with Transformers or other deep learning models
- Experience mentoring others
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
- Experience working with Product orgs
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.
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