Senior Machine Learning Engineer - Data Science & Machine Learning

Squarespace•New York City, NY

23h•Hybrid

About The Position

The Data Science & Machine Learning team is looking for a Machine Learning Systems Engineer to scale and support our team capabilities. We are modeling experts who solve business challenges with durable data science solutions. We work cross-functionally to enable Squarespace to integrate data science models into the product and the company. You will work closely with other Machine Learning Engineers to develop and maintain the machine learning platform that underpins all production data science models to unlock value for Squarespace and its customers. You will also have the opportunity to design, train, and update models alongside Data Scientists. The Machine Learning Systems function is focused on Data Scientist success: our goal is to enable Data Scientists to move fast and succeed, whether via tooling, partnership, or hands-on operational support. This is an opportunity for you to play a role in the deployment, scaling, and evolution of machine learning models using Google's Vertex AI platform. You will contribute to the strategy and implementation work to enable and unlock our growing machine learning capabilities. This is a hybrid role working from our NYC office 3 days per week. You will report to the Manager of Machine Learning Systems.

Requirements

Bachelor's Degree with 4+ years of experience working in a Machine Learning or similar role
Strong competency with Python, proficiency with SQL
Experience with cloud platforms. Knowledge of Google Cloud Platform and Vertex AI is a plus
Experience deploying and scaling ML models in production. Experience training models is a plus.
Knowledge of emerging ML technologies, tools, and industry best practices (e.g. vector databases, embedding models, open-source ecosystems)

Responsibilities

Collaborate with Data Scientists, ML Engineers, Site Reliability Engineers, and Product Engineers to identify opportunities and work around constraints to deliver ML systems
Deploy, monitor, evaluate, and optimize production machine learning models in 24/7 customer-facing applications.
Pair with team members or independently execute model training and updates
Implement scalable and reliable systems to handle model inference at scale
Develop and maintain automated pipelines for model training, testing, and deployment
Improve CI/CD practices to enable rapid and reliable model updates to speed up iterative learning
Respond to alerts and troubleshoot issues related to model deployment and infrastructure
Design and develop robust endpoint APIs to enable software engineers across the product to integrate ML APIs into applications
Develop, deploy, maintain and extend new technologies to enable and enhance data scientists' capabilities for every step of the ML model life cycle

Benefits

A choice between medical plans with an option for 100% covered premiums including medical, dental, and vision
Supplemental Life and Disability Insurance plans
Fertility and adoption benefits
Headspace mindfulness app subscription
Global Employee Assistance Program
Retirement benefits with employer match
Flexible paid time off
12 weeks paid parental leave and family care leave
Pretax commuter benefit
Education reimbursement
Employee donation match to community organizations
8 Global Employee Resource Groups (ERGs)
Dog-friendly workplace
Free lunch and snacks
Private rooftop
Hack week twice per year