Reddit

Engineering Manager, Ads ML Efficiency | JobSetuu

Reddit

USA
['Full-Time']

Posted 3 hours ago • Via jobicy.com

Description

Job Overview

  • Source: Jobicy

Job Description

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 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence.

About the Role

Reddit is building a dedicated Ads ML Efficiency function to make model training and inference materially faster, cheaper, safer, and more scalable. As the Engineering Manager for this team, you will lead a group focused on model optimization, training efficiency, GPU enablement, load testing, model performance tooling, and efficiency guardrails across Ads ML.

This role sits at the intersection of ML modeling, systems optimization, and organizational leverage. You will partner closely with ranking teams, ML Platform teams and serving owners to identify the highest-value bottlenecks, land measurable efficiency wins, and build the tooling and operating mechanisms that make those wins repeatable.

What you’ll do:

  • Lead & Grow: Hire, mentor, and retain a high-performing team of ML engineers / systems-oriented engineers working on model optimization and ML efficiency.
  • Set Technical Direction: Define the roadmap for training optimization, inference optimization, launch-readiness tooling, and reusable efficiency primitives across Ads ML.
  • Deliver Measurable Wins: Drive reductions in model training time, online latency, serving cost, and infra-driven launch risk.
  • Build Systems and Tooling: Guide the development of profiling, benchmarking, load testing, observability, cost analysis, debugging, and efficiency certification systems.
  • Operate in the Critical Path: Partner with model owners and platform teams to accelerate high-priority launches and remove bottlenecks from the path to production.
  • Shape the Team’s Evolution: Balance near-term white-glove optimization work with medium-term platformization and automation.
  • Build XFN Alignment: Work closely with MLP, AMP, Ranking, and serving teams to clarify boundaries, upstream generic wins, and keep Ads needs on track.
  • Raise the Bar: Establish engineering rigor around measurement, performance debugging, launch safety, and technical decision-making for efficiency work.

What we’re looking for:

  • Deep ML Engineering Experience: The candidate should have been close to the models themselves and understand training, serving, debugging, and optimization in depth.
  • Hands-on Optimization Background: Direct experience improving training loops, serving systems, profiling workflows, model/inference efficiency, or GPU utilization.
  • Strong Managerial Ability: Experience building and leading teams, coaching engineers, managing delivery, and making prioritization tradeoffs under ambiguity.
  • Distributed Systems Fluency: Proven ability to reason about production-scale ML systems and the tradeoffs that govern reliability, speed, cost, and scale.
  • Customer and Platform Instincts: Able to work as a service provider to modeling teams while still building reusable systems rather than only heroic one-offs.
  • Strong Communication: Can explain technical tradeoffs clearly to engineers, PMs, and senior stakeholders.
  • Ads experience: Experience in ads ranking, recommender systems, marketplace ML, or adjacent production ML domains is strongly preferred.

Nice-to-have:

  • Experience with GPU training and serving migrations.
  • Experience with PyTorch, distributed training frameworks, or kernel/performance optimization.
  • Experience building efficiency benchmarking or launch certification frameworks.
  • Experience working in organizations where ML platform and applied modeling responsibilities are split across multiple teams.

Benefits:

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k with Employer Match
  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave 

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.

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.

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.

Expert Career Tips for Engineering Manager, Ads ML Efficiency Roles

To succeed in a competitive market as a Engineering Manager, Ads ML Efficiency, you need more than just technical skills. Here are some expert strategies to elevate your profile:

  • Build a Strong Portfolio: For technical roles, a clean GitHub or a personal project site is essential. For non-technical roles, a case study portfolio demonstrating problem-solving and impact is equally valuable. Show, don't just tell, what you have achieved in your previous positions.
  • Master the Narrative: When interviewing, use the STAR method (Situation, Task, Action, Result) to structure your answers. Quantify your results wherever possible—mentioning "increased efficiency by 20%" is much more impactful than saying "improved efficiency."
  • Continuous Learning: The industry moves fast. Whether it's staying updated with the latest AI tools or mastering a new management methodology, continuous professional development is key. Consider obtaining industry-recognized certifications that align with Engineering Manager, Ads ML Efficiency requirements.
  • Networking: Connect with other professionals in similar roles. Join online communities, attend webinars, and engage in meaningful discussions on professional social networks. Often, the best opportunities come through referrals and community engagement.
  • Soft Skills Matter: Communication, empathy, and leadership are often the deciding factors between two equally qualified technical candidates. Cultivate these skills as they are universally valued across all industries and seniority levels.

Additionally, research the specific company's culture and values. Tailoring your application to show how you align with their mission can significantly increase your chances of moving forward in the process.

Salary & Compensation

Salary not disclosed; typically competitive for the role.

Work Arrangement

Type: On-Site

Standard business hours at the office.

Comprehensive Application Strategy & Hiring Process

Applying for a new role is a marathon, not a sprint. Follow this strategic approach to maximize your success rate:

1. Initial Research & Tailoring

Don't send the same resume to every employer. Spend at least 30 minutes researching the company. Look for recent news, their product roadmap, and their team structure. Modify your summary and core competencies to reflect the specific keywords found in the job description.

2. The Perfect Cover Letter

If the application allows for a cover letter, use it to tell a story that your resume cannot. Explain why you are passionate about this specific company and how your unique background makes you the perfect fit for the challenges they are currently facing.

3. Navigating the Multi-Stage Interview

Most modern hiring processes involve 3-5 stages. This typically includes a recruiter screen, a technical or skill-based assessment, a peer interview, and a final leadership round. Prepare for each stage differently: focus on enthusiasm and fit for the recruiter, technical depth for the assessment, and strategic vision for the leadership round.

4. Post-Interview Follow-Up

Always send a personalized thank-you note within 24 hours of each interview. Reference a specific topic discussed during the call to demonstrate your active listening and genuine interest in the role.

By following these steps, you demonstrate a high level of professionalism and attention to detail that sets you apart from the average applicant.

Typical Interview Process

  1. Resume screening
  2. HR call
  3. Skill interview
  4. Final manager interview
  5. Offer

Tip: Research the company's products and culture.

Global Market Intelligence & Relocation Insights

At JobSetuu, we specialize in helping talent navigate the global job market. Here is what you need to know about the current landscape in Global and beyond:

The demand for skilled professionals is increasingly borderless. For roles based in Global, understanding the local cost of living, visa requirements (if applicable), and cultural nuances is vital. If this is a remote role, consider the time zone alignment and the asynchronous communication culture of the hiring organization.

Relocation Support: Many forward-thinking companies offer relocation packages that include moving stipends, temporary housing, and legal assistance with work permits. When evaluating an offer, look beyond the base salary—consider the total compensation package, including equity, bonuses, and healthcare benefits.

Work-Life Balance Trends: Hybrid and remote work have become standard in many regions. Research the local labor laws and common practices regarding work hours and vacation time to ensure the role aligns with your lifestyle goals.

Leveraging JobSetuu's tools can help you compare salaries across different cities and understand the "purchasing power" of your potential offer, ensuring you make an informed decision for your long-term career path.

Skills & Competency Roadmap for Professional Development

To remain competitive in Professional Development, we recommend focusing on the following core competencies over the next 12-18 months:

  • Technical Mastery: Deepen your expertise in the core tools and languages relevant to your field. For developers, this might be cloud architecture; for marketers, it might be data-driven attribution modeling.
  • AI Augmentation: Learn how to leverage generative AI and automation tools to increase your productivity. Understanding how to integrate these technologies into your workflow is becoming a non-negotiable skill.
  • Leadership & Strategy: Even in individual contributor roles, the ability to think strategically and lead projects from inception to completion is highly valued. Focus on stakeholder management and high-level project planning.
  • Data Literacy: The ability to interpret data and use it to drive decisions is essential across all business functions. Familiarize yourself with data visualization and basic analytical concepts.

By investing in these areas, you not only prepare yourself for the role you are applying for today but also build a resilient foundation for the opportunities of tomorrow.

Apply via JobSetuu

Discover your next career milestone on JobSetuu. This Engineering Manager, Ads ML Efficiency position is part of our commitment to bringing you the most relevant and high-impact job openings globally. At JobSetuu, we simplify your job search by aggregating premier listings and providing the tools you need to stand out. Don't miss the chance to elevate your professional journey—explore more opportunities and career insights on our platform today.

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