As a company, Reddit primarily generates revenue through advertising, and we're working towards building a massive business to fund our mission. We distinguish ourselves from other digital ad platforms by attracting advertisers who want to connect with a specific target audience because of our passionate and engaged communities.
Ads prediction team’s mission is to predict ads engagement rates used in auctions to maximize ad engagements and marketplace efficiency. This team owns a critical piece in the ads delivery pipeline and machine learning infrastructure. Some examples projects:
- Improve our model through model architecture engineering work including exploring different state-of-the-art model architectures
- Systematic feature engineering work to build power features from Reddit’s data with aggregation, embedding, sub-models, content understanding techniques, etc.
- Build efficient ML infrastructures and tools such as auto ML flows, batch feature engineering framework, to facilitate our ML dev efficiency
As a Senior machine learning engineer in the Ads prediction team, you will research, formulate and execute on our mission to deliver the right ad to the right user under the right context with data and ML driven solutions.
Your Responsibilities:
- Building industrial-level models for critical ML tasks with advanced modeling techniques
- Research, implement, test, and launch new model architectures including deep neural networks with advanced pooling and feature interaction architectures
- Systematic feature engineering works to convert all kinds of raw data in Reddit (dense & sparse, behavior & content, etc) into features with various FE technologies such as aggregation, embedding, sub-models, etc.
- Be a mentor and cross-functional advocate for the team
- Contribute meaningfully to team strategy. We give everyone a seat at the table and encourage active participation in planning for the future.
Who You Might Be:
- Tracking records of consistently driving KPI wins through systematic works around model architecture and feature engineering
- 3+ years of experience with industry-level deep learning models
- 3+ years of experience with mainstream ML frameworks (such as Tensorflow and Pytorch)
- 4+ years of end-to-end experience of training, evaluating, testing, and deploying industry-level models
- 4+ years of experience of orchestrating complicated data generation pipelines on large-scale dataset
- Experience with Ads domain is a plus
- Experience with recommendation system is a plus
Benefits:
- Comprehensive Healthcare Benefits
- 401k Matching
- Workspace benefits for your home office
- Personal & Professional development funds
- Family Planning Support
- Flexible Vacation (please use them!) & Reddit Global Wellness Days
- 4+ months paid Parental Leave
- Paid Volunteer time off
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.
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.
