[![Image]() Meet Jobicy Copilot — free AI autofill for job applications + remote job alerts ›](#) [All remote jobs](https://jobicy.com/jobs.md)Open role[![Reddit logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2020/10/Reddit.jpg)](https://jobicy.com/company/reddit.md)Remote opportunity at[Reddit](https://jobicy.com/company/reddit.md) # Ads Conversion Modeling, Machine Learning Engineering Manager Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/reddit.md)Share8 Sep 2026Published48Listing views2Application actions8 Oct 2026Apply before Opportunity details ## About this role. AI SummaryReddit is hiring an Engineering Manager to lead its Ads Conversion Modeling team, which builds production machine-learning models that predict lower-funnel actions such as purchases, signups, and add-to-cart events. The manager will set the technical vision and roadmap, oversee the end-to-end model lifecycle, and lead and develop a high-impact ML engineering team. Core technical requirements include deep learning, large-scale ranking or recommendation systems, conversion modeling, data pipelines, and TensorFlow or PyTorch. The role requires close collaboration with product management, data science, and Ads engineering partners, and is remote for candidates located anywhere in the United States. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a senior people-management role in a technically demanding ads ML domain, requiring both hands-on credibility in large-scale conversion/ranking systems and ownership of a strategic roadmap. Success depends on delivering measurable business impact while managing complex cross-functional and production-modeling tradeoffs. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianHighly competitive$276,000US market range$230k–$322k0$354k AI insightThe posted US base-salary range is $230,000 to $322,000 USD yearly, producing an offer median of $276,000. This range is consistent with a senior Engineering Manager leading specialized ads machine-learning and ranking systems at a large US technology company; equity and possible commission are additional compensation and are not included in the base-salary figures. ## Core skills Skills and capabilities most closely associated with this opportunity. [Machine Learning Leadership](https://jobicy.com/jobs?search_keywords=Machine%20Learning%20Leadership.md)[Ads Conversion Modeling](https://jobicy.com/jobs?search_keywords=Ads%20Conversion%20Modeling.md)[Learning to Rank](https://jobicy.com/jobs?search_keywords=Learning%20to%20Rank.md)[Deep Learning](https://jobicy.com/jobs?search_keywords=Deep%20Learning.md)[PyTorch](https://jobicy.com/jobs?search_keywords=PyTorch.md)[TensorFlow](https://jobicy.com/jobs?search_keywords=TensorFlow.md)[Recommendation Systems](https://jobicy.com/jobs?search_keywords=Recommendation%20Systems.md)[ML Infrastructure](https://jobicy.com/jobs?search_keywords=ML%20Infrastructure.md)[Data Pipelines](https://jobicy.com/jobs?search_keywords=Data%20Pipelines.md)[People Management](https://jobicy.com/jobs?search_keywords=People%20Management.md) Sample interview questionsHow would you define a technical roadmap for an ads conversion-modeling team?I would begin with business objectives and current funnel metrics, then identify the highest-impact modeling, data-quality, serving, and experimentation gaps. I would sequence investments into near-term measurable improvements and longer-term platform capabilities, with clear model KPIs, ownership, dependencies, and risk management. Describe how you would evaluate a new conversion prediction model before and after deployment. Offline, I would evaluate calibrated predictive performance, ranking quality, segment stability, and robustness to delayed or sparse labels. Online, I would use controlled experiments to measure incremental conversion and advertiser outcomes while monitoring latency, spend distribution, calibration, fairness, and system reliability. What are key challenges in training large-scale lower-funnel conversion models? Common challenges include severe label sparsity, delayed attribution, selection bias, nonstationary user and advertiser behavior, and leakage across time windows. I would address these through disciplined data definitions, temporal validation, calibrated objectives, bias-aware sampling or weighting, strong monitoring, and frequent retraining where justified. How do you balance people leadership with maintaining technical depth as an engineering manager? I establish clear ownership and empower senior engineers to lead designs, while staying engaged in architecture reviews, model evaluation standards, and critical execution decisions. I reserve regular time for coaching, roadmap work, and technical learning so that I can remove obstacles without becoming a bottleneck. How would you handle disagreement between product stakeholders and ML engineers about a model investment? I would make the decision framework explicit by clarifying the user or advertiser outcome, expected impact, required evidence, engineering cost, and opportunity cost. Where uncertainty remains, I would propose a scoped experiment or milestone-based prototype that produces data quickly and enables a transparent decision. 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 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit [www.redditinc.com](http://www.redditinc.com/). Reddit’s lower funnel business is rapidly growing and pushing the heavy ranking web conversion models towards state-of-the-art is critical for continued growth. The Conversion modeling Team plays a pivotal role in developing and maintaining machine learning models that drive user conversions from Reddit Ads, with a special focus on predictive modeling around interactions like purchase, signup, add to cart, and other lower funnel user actions. As we expand our machine learning infrastructure and incorporate new engagement signals, we are looking for a skilled Engineering Manager who can lead this critical team. 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. ### Target Skills and Expertise The Engineering Manager (EM) will be responsible for defining the team’s vision, setting strategic direction, and executing a technical roadmap for conversion modeling at Reddit. This involves: * Model Architectures: Expertise in architecting and implementing deep learning models, with experience in ranking, recommendation, or conversion modeling. * ML Frameworks: Proficiency with mainstream ML libraries (TensorFlow, PyTorch). * End-to-End ML Lifecycle: Experience in training, testing, and deploying production-grade machine learning models. * Data Pipelines: Experience orchestrating large-scale data generation and processing pipelines. * Ads domain Experience: Experience in interaction of ranking model with rest of Ads systems like bidding, auction, retrieval etc * Ads Modeling (Preferred): Background in ads modeling or familiarity with engagement prediction models in the ads domain is beneficial. Role responsibilities: 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. * Technical Domain Knowledge: Experience with Ads conversion modeling, ranking (heavy ranker experience) & recommendations experience is required. * 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 conversion 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 #LI-AS1 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/](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. The base salary range for this position is: $230,000—$322,000 USD 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](https://redditinc.com/policies/candidate-privacy-policy). 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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