Senior Machine Learning Engineer, Conversion Lift

2 Days ago • 5 Years + • $216,700 PA - $303,400 PA

Job Summary

Job Description

As a Senior Machine Learning Engineer, Causal Inference on the Ads Measurement team, you will lead the Reddit Conversion Lift (RCL) product, focusing on improving causal inference/ML methodology, reliability, and scalability. Responsibilities include leading projects, enhancing ad measurement capabilities, designing and maintaining experimentation systems, developing statistical and machine learning models, collaborating with stakeholders, and mentoring junior team members. The role requires staying updated on the latest causal inference, causal ML, and machine learning techniques.

Must have:

5+ years of experience in a relevant industry or academic background.
Experience deploying models in production settings.
Strong understanding of advertising domain.
Strong understanding of causal inference and experimental design.
Ability to lead and mentor machine learning engineers.
Strong communication skills.

Good to have:

Advanced degree in a quantitative field.
Deep understanding of advanced causal inference.
Experience designing and developing scaled experimentation systems.
Tech lead experience on cross-functional engineering teams.
Direct experience with ad effectiveness measurement.

Perks:

Comprehensive Healthcare Benefits and Income Replacement Programs
401k Match
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Reddit Global Days off
Generous paid Parental Leave
Paid Volunteer time off

4 skills required

4 skills required for this role

Add these skills to join the top 1% applicants for this job

data-science

communication

scalability

cross-functional

Job Details

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 101M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit redditinc.com.

The Ads Measurement team is dedicated to evaluating and improving advertising effectiveness to drive advertiser success. This team is responsible for developing measurement products and infrastructure to enable advertisers to understand the value that Reddit drives for their business.

As a Machine Learning Engineer, Causal Inference on the Ads Measurement team, you will lead our Reddit Conversion Lift (RCL) product, driving major improvements in Casal Inference/ML methodology, reliability and scalability.

Responsibilities:

Lead projects from concept, design, implementation, to rollout, ensuring the highest quality and performance.
Identify opportunities to enhance ad measurement capabilities by diving deep into our platform and understanding the needs of our advertisers.
Design, implement, and maintain high-reliability experimentation systems.
Conduct code reviews, maintain high engineering standards, and build scalable systems
Design and develop statistical and applied machine learning models to measure ad effectiveness
Collaborate with cross-functional stakeholders, including ads product, product marketing, measurement engineering, data science and Marketing Science.
Mentor junior team members, share knowledge, and contribute to the technical growth of the team. Provide guidance on causal inference and machine learning best practices and methodologies.
Stay up-to-date on state-of-the-art casual inference, causal ML, and machine learning techniques; recognize promising innovations; and, adapting them to Reddit's unique platform and community.

Minimum Qualifications:

5+ years of experience in a relevant industry or academic background, preferably in a quantitative/modeling or highly scalable computing environment. For candidates with a PhD, at least 2+ years of industry experience in a MLE or engineering role.
Experience deploying models in production settings and working with ML or experimentation infrastructure
Strong understanding of advertising domain
Strong understanding of causal inference and experimental design, including intent-to-treat estimators, ghost ads, and propensity score modeling.
Ability to lead and mentor machine learning engineers, software engineers, and/or data scientists.
Strong communication skills to collaborate effectively with cross-functional teams and stakeholders.
Demonstrated ability to innovate and stay updated with the latest advancements causal inference, machine learning and AI.

Preferred Qualifications:

Advanced degree (MS/PhD) in a quantitative field such as statistics, data science, computer science, economics, or operations research.
Deep understanding of advanced causal inference, including Bayesian experimental analysis, heterogenous treatment effects estimation, double machine learning, etc.
Experience designing and developing scaled experimentation systems
Tech lead experience on cross-functional engineering teams, guiding implementation of experimentation infrastructure and tooling
Direct experience with ad effectiveness measurement (e.g., conversion lift, brand lift, sales lift, split testing) is a plus

Benefits: