About this role.
Reddit is seeking a Machine Learning Engineering Manager to lead the Ads Engagement Modeling team. This role involves setting technical strategy, driving execution of ML models, and mentoring a high-performing team. The manager will collaborate cross-functionally with product managers, data scientists, and engineers to optimize user engagement through predictive models. Ideal candidates have deep ML expertise, experience with large-scale production systems, and a track record of leading technical teams.
Role DNA
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Job Complexity
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Core skills
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Cover letter sample
I am excited to apply for the Machine Learning Engineering Manager position on the Ads Engagement Modeling team at Reddit. With over 8 years of experience in machine learning and a strong background in leading high-impact teams, I am confident in my ability to drive engagement modeling innovation at scale.
At my previous role, I led a team of ML engineers to develop and deploy real-time prediction models that improved user engagement by 30%. My expertise in TensorFlow and PyTorch, combined with a strategic mindset, aligns perfectly with Reddit's goals.
I thrive in cross-functional environments and have a proven track record of partnering with product and data science teams to deliver business results. I am passionate about mentoring talent and fostering a culture of technical excellence.
Thank you for considering my application. I look forward to the opportunity to contribute to Reddit's mission of bringing community and belonging to every person in the world.
Sample interview questions
I have managed teams of up to 10 ML engineers, focusing on both technical growth and delivery. I conduct weekly one-on-ones, pair senior engineers with juniors, and set clear milestones. For example, during a model overhaul, I ensured knowledge transfer while meeting deadlines through agile sprints.
I would start by understanding business goals and current model gaps. I'd prioritize high-impact areas like CTR prediction and video view-through, and explore advanced techniques like transformers. I'd collaborate with product and data science to align on KPIs and iterate based on A/B test results.
I led a project to reduce latency in a real-time ad prediction system by 40% through model quantization and feature pruning. My team redesigned the feature pipeline and optimized inference code. The result was a 15% increase in ad revenue due to faster delivery.
I regularly read papers, attend conferences, and run small experiments in a sandbox environment. I select techniques that offer clear performance gains and feasibility. For instance, we adopted attention mechanisms after seeing a 5% lift in offline metrics.
Two engineers disagreed on model architecture choice. I facilitated a meeting where each presented pros/cons, then proposed a short experiment to compare both. The experiment showed one approach was slightly better, and the team accepted the decision. This fostered a data-driven culture.
Team overview:
The Engagement Modeling Team at Reddit focuses on building machine learning models to drive on-platform user engagement with diverse media and content, with a focus on predictive modeling to improve interactions of click-throughs and video view-throughs. This role offers a unique opportunity to shape and scale Reddit’s Ads prediction models, in alignment with our product goals and driving SoTA modeling advancement.
This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders.
We’re a remote-friendly company, and this position is open to candidates anywhere in the U.S.
Responsibilities:
- Set Technical Vision and Strategy: Define and execute a roadmap for engagement modeling, balancing innovative modeling approaches with business objectives.
- Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
- Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
- Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
- Innovate in ML Architecture: Implement and optimize model architectures tailored to engagement prediction, leveraging deep learning and advanced ML techniques.
Candidate Profile:
The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have:
- People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth.
- Set Technical Vision and Strategy: Ability to plan and execute a long-term technical strategy aligned with business objectives. Define and execute a roadmap for conversion modeling, balancing innovative modeling approaches with business objectives.
- Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
- Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
- Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
- Innovate in ML Architecture: Implement and optimize model architectures tailored to conversion prediction, leveraging deep learning and advanced ML techniques.
Required qualifications:
- At least 2+ of experience building and managing high-performing machine learning teams, ideally in the Ads domain. Will consider tech lead experience as well
- Deep ML Expertise: Deep hands-on experience working with machine learning models and deploying them in large-scale production systems. Proven ability in training, evaluating, and deploying large-scale models.
- End-to-End ML Lifecycle Experience: Proven ability in training, evaluating, and deploying large-scale models.
- 4+ years of hands-on experience with TensorFlow or PyTorch.
- Strategic Thinking: Ability to develop and communicate a clear, compelling technical strategy that supports broader company objectives and addresses the needs of internal customers.
- Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI solutions that drive business value.
- Exceptional Communication & Collaboration: Strong interpersonal skills and a collaborative mindset, with the ability to effectively communicate complex technical topics to diverse audiences and build strong relationships with cross-functional partners
- Experience with Ads or Engagement Modeling is a plus.
Perks and Benefits:
- 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
- Competitive salary and equity options
- Comprehensive health benefits (medical, dental, vision) & workplace perks (home office set up stipend etc)
- Generous 401k matching
- Flexible vacation policy
- Paid parental leave (4+ months)
- Family planning support
- Paid volunteer time off
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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 salary 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.
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
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, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
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