Sr. Manager, Machine Learning Engineering – User Understanding
Job Description
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
The user understanding team builds cutting edge user understanding models and systems to deeply understand the evolving interests, intents and tastes of our 500M+ users, which power personalization of Pinterest products across Discovery (Homefeed, Search, Related Pins), Ads, Shopping and Growth. As the senior engineering manager of the user understanding team, you’ll set technical vision and lead the team to build the next generation user understanding models and systems, and work with many cross functional partners to deliver more relevant and personalized results to our pinners.
What you will do:
- Lead a team of experienced ML & backend engineers to build cutting edge user understanding models and systems, which are widely incorporated in Pinterest products across Discovery (Homefeed, Search, Related Pins), Ads, Shopping and Growth.
- Partner closely with vertical teams across Pinterest to experiment new ML models / systems and deliver end-to-end metric impact.
- Be a thought leader on user modeling and recommender systems, set and execute technical vision, and improve state-of-the-art technology.
- Partner with stakeholders to expand impact across the company, including product management, data scientists and design.
- Hire, mentor and grow managers, leaders and engineers on the team. Build a culture of excellence and expertise.
What we are looking for:
- Experience leading eng teams on large-scale ML recommendation or ads systems.
- Domain expertise on ML. Experience in areas such as user modeling, NLP and recommendation systems is a bonus.
- Ability to drive the roadmap and directions of scalable production quality systems end-to-end.
- 5+ years of experience managing an ML engineering team working on production ML systems. 10+ years of industry experience.
- Bachelor’s or Master’s degree in a relevant field such as computer science, or equivalent experience.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
In-Office Requirement Statement:
- We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
#LI-HYBRID
#LI-AK7
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
Our Commitment to Inclusion:
Interested in this job?
Applications are no longer being accepted for this job.
Safe Remote Job Search Tips
Verify Employer Thoroughly
Research the company's identity thoroughly before applying. Check for a professional website with contacts, active social media, and LinkedIn profiles. Verify details across platforms and look for reviews on Glassdoor or Trustpilot to confirm legitimacy.
Never Pay to Get a Job
Legitimate employers never require payment for applications, training, background checks, or equipment. Always reject upfront payment requests or demands for bank details, even if they claim it's for purchasing necessary work gear on your behalf.
Safeguard Your Personal Information
Protect sensitive data like SSN, bank details, or ID copies. Share this only after accepting a formal, written job offer. Ensure it's submitted via a secure company system or portal, never through insecure channels like standard email attachments.
Scrutinize Communication & Interviews
Watch for communication red flags: poor grammar, generic emails (@gmail), vague details, or undue pressure. Be highly suspicious of interviews held only via text or chat apps; legitimate companies typically use video or phone calls.
Beware of Unrealistic Offers
If an offer's salary or benefits seem unrealistically high for the work involved, be cautious. Research standard pay for similar roles. Offers that appear 'too good to be true' are often scams designed to lure you into providing information or payment.
Insist on a Formal Contract
Always secure and review a formal, written job offer or employment contract before starting work or sharing final personal details. Ensure it clearly defines your role, compensation, key terms, and conditions to avoid misunderstandings or scams.