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We’re evolving and continuing our mission to bring community, belonging, and empowerment to everyone in the world. Providing a delightful and relevant experience to our users applies to our Ads like all of our offerings, and we’re excited to build a product that is best-in-class for our users and advertisers. The year ahead is a busy one - join us!
Ads Targeting ML engineers are focused on designing and implementing ML systems and solutions for improving targeting products. The team’s projects involve building large-scale offline & online retrieval systems across several dimensions to improve contextual & behavioral targeting for targeting products.
As a senior machine learning engineer in the ads targeting core team, you will execute our mission to automate targeting and deliver the most relevant audiences to advertisers under the right context with data and ML-driven solutions.
Your Responsibilities:
- Own end-to-end execution of ML-based targeting products like smart targeting expansion, keyword targeting, auto targeting, user lookalikes etc
- Own offline & online experimentation of ML models for improving targeting products to drive advertiser outcomes
- Research, implement, test, and launch new model architectures for retrieval using deep learning (GNNs, transformers, two tower models) with a focus on improving advertiser outcomes
- Drive technical roadmaps and lead day to day project execution, and contribute meaningfully to team vision and strategy
- Work on large scale data systems, backend services and product integration
- Collaborate closely with multiple stakeholders cross product, engineering, research and marketing
Required Qualifications
- 2+ years of experience with industry-level deep learning models.
- 2+ years of experience with mainstream ML frameworks (such as Tensorflow and Pytorch).
- 3+ years of end-to-end experience of training, evaluating, testing, and deploying industry-level models.
- 3+ years of experience of orchestrating complicated data generation pipelines on large-scale datasets.
- Experience working with cross functional stakeholders across research, product & infrastructure to productize ML research
- Knowledge of large scale search & recommender systems, or modern ads ranking/retrieval/targeting systems is preferred
- Experience with deep learning, representation learning or transfer learning is preferred
Benefits:
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k Match
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Reddit Global Days off
- Generous paid Parental Leave
- Paid Volunteer time off
#LI-AK1 #LI-REMOTE
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base pay range for this position is:
$185,800—$260,100 USD
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at ApplicationAssistance@Reddit.com.
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