Software Engineer III, Machine Learning
To see similar active jobs please follow this link: Remote Development jobs
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.
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 is responsible for predicting 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. Project highlights:
Model architecture engineering via exploring different state-of-the-art model architectures such as Multi-task learning, Attention Layer
Systematic feature engineering to build powerful features from Reddit’s data with aggregation, embedding, sub-models, content understanding techniques, etc.
Build efficient ML infrastructure and tools such as auto ML flows and batch feature engineering framework, to accelerate ML dev cycle
As a machine learning engineer in the Ads prediction team, you will research, formulate, and execute projects, and actively participate 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 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
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 Machine Learning models
3+ 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
Deep learning experience is a strong plus
Experience in orchestrating complicated data generation pipelines on large-scale dataset is a plus
Experience with Ads domain is a plus
Experience with Recommendation Systems 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
About the job
Software Engineer III, Machine Learning
To see similar active jobs please follow this link: Remote Development jobs
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.
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 is responsible for predicting 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. Project highlights:
Model architecture engineering via exploring different state-of-the-art model architectures such as Multi-task learning, Attention Layer
Systematic feature engineering to build powerful features from Reddit’s data with aggregation, embedding, sub-models, content understanding techniques, etc.
Build efficient ML infrastructure and tools such as auto ML flows and batch feature engineering framework, to accelerate ML dev cycle
As a machine learning engineer in the Ads prediction team, you will research, formulate, and execute projects, and actively participate 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 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
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 Machine Learning models
3+ 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
Deep learning experience is a strong plus
Experience in orchestrating complicated data generation pipelines on large-scale dataset is a plus
Experience with Ads domain is a plus
Experience with Recommendation Systems 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