Founding Machine Learning Engineer, Domains Search at Squarespace

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

06 Apr, 26

Salary

236500.0

Posted On

06 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Natural Language Processing, Search Systems, Retrieval, Ranking, Recommendation Systems, Architectural Judgment, ML Systems Deployment, Index Design, Query Parsing, Learning-to-Rank, Multi-Objective Optimization, Embedding Models, Collaboration, Technical Direction, Generative AI

Industry

Software Development

Description

The Domains Search team at Squarespace is building the next generation of intelligent search experiences for helping customers find the perfect domain. From leveraging large language models to generate creative domain suggestions, to building scalable ranking and personalization systems, our team sits at the intersection of applied machine learning, natural language processing, and large-scale search & recommendation infrastructure. We are looking for Senior Machine Learning Engineers to build our search platform from the ground up with focuses on retrieval and ranking. You will report to the Engineering Manager of the Domains Search team in our New York City headquarters. Why Join Us This is a unique opportunity to shape a greenfield ML initiative at Squarespace. As part of a small, high-impact team, you'll have influence over how we build our search platform and how millions of customers discover their online identity. If you've wanted to build a next generation of search system with few legacy constraints, we'd love to hear from you. You'll Get To... Be one of our founding MLEs, owning key parts of this scope (retrieval or ranking) and contributing across the stack as the team grows. Design, build, and deploy hybrid search systems (classical ML + genAI + rule-based) for generative domain name search which balance relevance, latency, and scale. Lead technical direction in retrieval (index design, query parsing, retrieval strategies) or ranking (learning-to-rank, multi-objective optimization). Lead embedding model selection, post-training optimization, and evaluation to power both semantic retrieval and ranking features. Collaborate with engineers, data scientists, and product managers to translate ambiguous product ideas into technical approaches (including build vs. buy decisions). Who We're Looking For 5+ years of professional experience in machine learning engineering, with at least 2 years focused on search, retrieval, ranking, or recommendation systems. Experience building production search or ranking systems end-to-end, whether standing up new systems or leading architectural shifts. Depth in two or more of: retrieval (indexing, vector search), ranking (learning-to-rank, multi-objective optimization), or embeddings. LLM integration is a plus. Comfort owning strategy to help shape our roadmap while building high-quality technical solutions. Strong architectural judgment, with an ability to evaluate tradeoffs and communicate decisions clearly to both technical and non-technical stakeholders. Proven ability deploying and operating ML systems at scale, ensuring reliability, performance, and quality under high traffic volumes. Benefits & Perks A choice between medical plans with an option for 100% covered premiums Fertility and adoption benefits Access to supplemental insurance plans for additional coverage 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 Cash Compensation Range: $128,500 - $236,500 USD The base salary for this position will vary based on job-related criteria including relevant skills, experience, and location, among other factors. In addition to the cash compensation above (which includes base salary and, where applicable for eligible roles, may include overtime pay), Squarespace employees are eligible to be granted an option to purchase our common stock. Sales positions generally offer a competitive On Target Earnings (OTE) incentive structure in addition to base salary. About Squarespace Squarespace is a design-driven platform helping entrepreneurs build brands and businesses online. We empower millions of customers in more than 200 countries and territories with all the tools they need to create an online presence, build an audience, monetize, and scale their business. Our suite of products range from websites, domains, ecommerce, and marketing tools, as well as tools for scheduling with Acuity and creating and managing social media presence with Bio Sites and Unfold. Our team of more than 1,700 is headquartered in New York City, with offices in Dublin, Ireland, and Aveiro, Portugal. For more information about our company, visit https://www.squarespace.com/about/careers. Our Commitment Today, more than a million people around the globe use Squarespace to share different perspectives and experiences with the world. Not only do we embrace and celebrate the diversity of our customers, but we also work toward the same in our employees. At Squarespace, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, national origin, gender, sex, gender identity or expression, sexual orientation, age, citizenship, marital or parental status, disability, veteran status, or other class protected by applicable law. We are proud to be an equal opportunity workplace. #LI-Hybrid Thank you in advance for providing the following details about your work history from your resume! This helps us ensure that your candidate information is accurate and consistent during the hiring process. Squarespace will never solicit your personal banking information or ask you to transfer money in connection with a job offer or interview. We also will not reach out to you via phone or SMS without your permission or knowledge.

Responsibilities

You will design, build, and deploy hybrid search systems for generative domain name search. Additionally, you will lead technical direction in retrieval or ranking and collaborate with cross-functional teams.