Machine Learning Engineer II, Content Evaluation

Company Description
Etsy is the global marketplace for unique and creative goods. We build, power, and evolve the tools and technologies that connect millions of entrepreneurs with millions of buyers around the world. As an Etsy Inc. employee, whether a team member of Etsy, Reverb, or Depop, you will tackle unique, meaningful, and large-scale problems alongside passionate coworkers, all the while making a rewarding impact and Keeping Commerce Human.

Salary Range:

What’s the role?

Etsy is hiring a Machine Learning Engineer II to join the Trust & Safety Content Evaluation team, a machine learning team that supports Etsy's ability to detect policy violations in user-generated content. Our team works to keep Etsy a trusted and safe place for our members, detecting violations in real-time. This position involves developing multiple complex projects, using strong communication skills to work with applied scientists and machine learning engineers. You will also partner with cross-functional stakeholders from different backgrounds and technical levels.

Do you find joy in solving difficult problems in machine learning involving distributed systems, varied data sources, and multiple collaborators? This is a fantastic opportunity for someone interested in developing systems that will support Etsy's safety for years to come, evaluating hundreds of millions of unique, handmade, vintage listings.

This is a full-time position reporting to the Senior Manager of Engineering, Content Evaluation. In addition to salary, you will also be eligible for an equity package, an annual performance bonus, and our competitive benefits that support you and your family as part of your total rewards package at Etsy.

For this role, we are considering candidates based in the United States. Candidates living within commutable distance of Etsy’s Brooklyn Office Hub, or in the San Francisco Bay Area, may be the first to be considered. For candidates within commutable distance, Etsy requires in-office attendance once or twice per week depending on your proximity to the office. Etsy offers different work modes to meet the variety of needs and preferences of our team. Learn more details about our  work modes and workplace safety policies here.

What’s this team like at Etsy?

• The Content Evaluation squad within Trust & Safety Product Engineering works to automatically remove dangerous and risky member-generated content from our marketplaces

• We work closely with other Trust & Safety partners in Product, Design, Engineering and Operations, as well as with our Machine Learning Enablement, Inventory and Quality engineering teams.

• This year, we are focusing on ensuring the safety of conversations between our sellers and buyers, and on building models to understand the role sellers have in the production of their products. In other words we build the foundational trust that ‘makes Etsy Etsy’  

What does the day-to-day look like?

• Prototype, optimize, and scale large-scale multimodal ML models to improve precision and recall of our evaluations core business metrics.

• Work with state of the art LLM / genAI techniques to drive innovation in Trust & Safety.

• Design and implement experiments (Hypothesis testing, A/B testing etc.) to measure marketplace effects 

• Coach and train junior team members

• Work closely with product managers, ML engineers, full-stack engineers, and designers to measure and improve our ads marketplace while driving value to our sellers 

• Collaborate with Product, Design, Research, Analytics, and others to craft plans that achieve our business goals, while delivering new evaluation and classification systems to match our evolving policy needs

• Of course, this is just a sample of the kinds of work this role will require! You should assume that your role will encompass other tasks, too, and that your job duties and responsibilities may change from time to time at Etsy's discretion, or otherwise applicable with local law.

Qualities that will help you thrive in this role are:

• An M.S. or Ph.D. degree in Computer Science or related engineering fields, and/or 3+ years of practical machine learning experience

• You have a track record of applying statistical techniques in addressing real-world problems.

• You are an expert in one of the following fields: text classification, image classification, multimodal machine learning, LLMs/genAI, active learning / human-in-the-loop, reinforcement learning 

• You have experience training, deploying, monitoring, debugging and iterating on production machine learning systems.

• You can successfully create requirements and lead your team from design through to delivery.

• You write understandable, testable code and you have an eye towards maintainability.

• You care about the implications of your work on end users.

• You value working with people who are curious, enthusiastic, generous, and responsible. 

Additional Information
 

What's Next
If you're interested in joining the team at Etsy, please share your resume with us and feel free to include a cover letter if you'd like. As we hope you've seen already, Etsy is a place that values individuality and variety. We don't want you to be like everyone else -- we want you to be like you! So tell us what you're all about.
 
Our Promise
At Etsy, we believe that a diverse, equitable and inclusive workplace furthers relevance, resilience, and longevity. We encourage people from all backgrounds, ages, abilities, and experiences to apply. Etsy is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status, or any other characteristic protected by applicable law. If, due to a disability, you need an accommodation during any part of the application or interview process, please let your recruiter know. While Etsy supports visa sponsorship, sponsorship opportunities may be limited to certain roles and skills.