Machine Learning Engineer, Ads Measurement
Remote - United States
Full Time Mid-level / Intermediate USD 260K+
“The front page of the internet," Reddit brings over 430 million people together each month through their common interests, inviting them to share, vote, comment, and create across thousands of communities. Come for the cats, stay for the empathy.
The Ads Measurement Core team is dedicated to enhancing the efficiency and user-friendliness of our advertising platform. We specialize in privacy enhancing technologies, identity resolution, and modeled conversions. We are looking for a Senior Machine Learning Engineer to use privacy enhancing technologies to improve our capabilities. As a diverse group of software engineers, product managers, data scientists, and ads experts, we are excited for you to join our team!
Responsibilities:
- Design and develop applied machine learning models for modeled conversions and identity matching from ideation to production deployment.
- Identify opportunities to enhance ad measurement capabilities by diving deep into our platform and understanding the needs of our advertisers.
- Collaborate with data scientists and backend software engineers
- Conduct A/B tests and experiments to iterate and fine-tune algorithms and models.
- Stay updated on state-of-the-art algorithmic techniques and recognize promising innovations, adapting them to Reddit's unique platform and community.
- Design, implement, and maintain reliable, high-performance distributed systems.
Minimum Qualifications:
- 3+ years of experience with applied machine learning models and large-scale ML systems. Includes experience, training, evaluating, testing, and deploying machine learning models
- Proficiency with programming languages (Python, SQL) and statistical analysis.
- Effective communication skills to collaborate with cross-functional teams and convey technical concepts to non-technical stakeholders.
Preferred Qualifications:
- Experience of orchestrating complicated data pipelines and system engineering on large-scale dataset
- Prior experience with Modeled Conversions, Ads Privacy, or Ads Measurement is a big plus
- Prior experience with Sequence Modeling, Reinforcement Learning, and Transformer Architecture is a big 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.
The base pay range for this position is:$185,800—$260,100 USDReddit 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.
Tags: A/B testing Architecture Data pipelines Distributed Systems Engineering Machine Learning ML models Pipelines Privacy Python Reinforcement Learning SQL Statistics Testing
Perks/benefits: 401(k) matching Career development Equity Flex vacation Health care Home office stipend Insurance Medical leave Parental leave
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