Senior Machine Learning Engineer, Ads Covernsion Modeling
Job Description
Reddit has a flexible first workforce! if you happen to live close to our physical office location 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 Netherlands or the United Kingdom.
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.
The Ads Conversions Modeling Team is entrusted with the development and maintenance of a diverse set of Machine Learning models that are responsible for predictions regarding user conversions after engaging with Reddit. The creation and enhancement of these models plays a crucial role in our organization’s efforts to optimize advertising effectiveness and drive business growth. We are looking for a motivated engineer that will help us advance our vision. As a diverse group of software engineers, product managers, data scientists, and ads experts, we are excited for you to join our team!
As a machine learning engineer in the Ads Conversion Modeling Team, you will take a leadership role in researching, formulating, and executing projects, while actively participating in the end-to-end implementation process. You will collaborate with cross-functional teams to ensure successful product delivery. You will also be able to contribute your expertise and shape the future of ads ML at Reddit!
Your Responsibilities:
- Building industrial-level models for critical ML tasks with advanced modeling architectures and 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.
- Contribute meaningfully to team strategy. We give everyone a seat at the table and encourage active participation in planning for the future
- 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
We’re committed to hiring the best talent and building a diverse team. We’re proud to be completely remote-friendly and will continue to offer remote work options beyond the pandemic.
Join us at Reddit, and help us build a community that is inclusive and empowering for everyone.
Benefits:
- Pension Savings plan
- Medical Plan
- Short term sickness benefits
- WIA excess and WGA gap insurance
- Workspace benefits for your home office
- Personal & Professional development funds
- Family Planning Support
- Flexible Vacation & Reddit Global Days Off
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 [email protected].
