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Senior Machine Learning Engineer, Ads Targeting

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Location
United States
Base Salary
217k-303k USD
Reddit

Job Description

Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 82M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit redditinc.com.

Reddit has a flexible first workforce! if you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely from the United States or Canada.

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.

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 leading applied machine learning models with Tensorflow/Pytorch with large-scale ML systems
  • 5+ years of end-to-end experience of training, evaluating, testing, and deploying machine learning models
  • Experience with large scale data processing pipeline orchestration tools like Spark, Dataflow, Kubeflow, Airflow, BigQuery
  • Experience working with nearest-neighbor search systems is a big plus
  • Experience building improving MLOps tools and ML experimentation workflows
  • 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
  • Tech lead experience in a product team is strongly preferred

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.

The base pay range for this position is:
$216,700$303,400 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.

Advice from our career coach

A successful applicant for this senior machine learning engineer position at Reddit should be familiar with leading applied machine learning models using Tensorflow or PyTorch and have experience with large-scale ML systems. To stand out as an applicant, showcase your expertise in training, evaluating, testing, and deploying machine learning models, as well as your experience with large-scale data processing pipeline orchestration tools like Spark, Dataflow, Kubeflow, Airflow, and BigQuery. Highlight any experience you have with nearest-neighbor search systems, MLOps tools, and ML experimentation workflows. Additionally, emphasize any tech lead experience you have in a product team and your knowledge of large-scale search recommender systems, modern ads ranking, retrieval, and targeting systems. Here are some specific tips to help you stand out:

  • Demonstrate your ability to own end-to-end execution of ML-based targeting products and experimentation of ML models
  • Showcase your experience in researching, implementing, and launching new model architectures for retrieval using deep learning
  • Highlight your success in driving technical roadmaps, leading project execution, and contributing to team vision and strategy
  • Provide examples of your collaboration with multiple stakeholders across product, engineering, research, and marketing
  • Emphasize any experience you have with deep learning, representation learning, or transfer learning

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