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

#LI-Remote

Team Description

Ad Safety is a growing team focusing on user safety and advertiser trust by building a robust, automated ecosystem that prioritizes Brand Suitability and Ads Integrity. This is achieved by deploying highly accurate automated ad review systems that vet content before it goes live, coupled with advanced brand safety classifications and controls that give brands granular agency over their ad adjacency along with ensuring Reddit standards are adhered to. By further integrating with trusted third-party verification partners, the platform not only solidifies confidence in its ad effectiveness but also creates a transparent, scalable environment designed to unlock significant revenue growth.

The team is expanding its Fraud counter-measures by consolidating the identification and enforcement of deceptive ads (Malware, Phishing, Scams) and Billing fraud into a centralized platform. Collecting signals across multiple surfaces, in addition to third party vendor integration, will allow for more effective measures to analyze coordinated efforts of bad actors and pre-emptive detection of malignant intent. 

Role Description

Reporting to the Ad Safety Engineering Manager, the person in this role will be the primary technical driver for the new Fraud detection system, working closely with Ad Review, Billing, Policy and other Reddit Safety teams to enhance overall systems. You will drive the long term strategy for the platform, setting measurable goals and taking overall ownership of a critical function in the Ads organization. 

This is a high-agency position for an engineer who can navigate ambiguity and take decisive ownership of the platform's technical direction in collaboration with other engineers, teams, and stakeholders. 

This role acts as both a technically adept deep coder and a force multiplier. It is responsible for working cross-functionally to help establish the long-term technical vision for Fraud Detection, ensuring our systems are highly available and capable of scaling with the marketplace. In this role you will lead large-scale projects through the entire software development lifecycle, from concept through implementation until delivery. 

What You’ll Do

• Steer: Work with the team to select, scope, and drive high-leverage projects that accelerate the development of Fraud Detection to help Reddit achieve its ambitious goals.
• Architect: Help define the 2+ year technical roadmap for the platform, translating complex business needs into a clear strategy for highly available and performant backend services.
• Build: Execute on a strategy to create world-class Fraud Detection systems.
• Amplify: Mentor, coach, and collaborate with other technical contributors, fostering a culture of empathetic technical excellence and proactive problem-solving.
• Collaborate: Work together with a variety of cross-functional teams, including Product Management, Policy and Legal, to ensure Fraud Detection meets the needs of all stakeholders.
• Evolve: Learn and improve technical and non-technical abilities, staying up-to-date on trends and best practices in the Fraud Detection space across the industry.

Qualifications

• Experience: 7+ years of software engineering experience, with a track record of leading large-scale technical projects that require cross-team and cross-functional collaboration.
• Backend Expertise: Strong experience in large-scale distributed systems and developing highly scalable and reliable backend services.
• Technical Ability: Expertise in at least one general-purpose programming language (e.g., Go, Python, Scala, Java, or C++) and ability to grow expertise in Python and Go.
• Leadership: Demonstrated ability to disambiguate complex problems, align stakeholders with different priorities, and aggressively prioritize to execute effectively.
• Communication: Excellent communication skills employed to drive toward consensus, navigate disagreements, and influence decisions across the engineering organization.
• Agency: A bias for action. The ability to identify what needs to be done, take the initiative to make it happen without waiting for direction, and finish the swing.

Preferred Qualifications

• Direct experience as a Tech Lead or in a similar function.
• Previous success as part of an Ads team with a user base in the millions.
• Experience in Ads Fraud, Ad review or Ads Brand Safety
• Proven experience designing, building, and operating scalable platforms.
• Expertise in Python and/or Go.
• Prior experience in Fraud/Malicious actors space
• Proven track record of utilizing LLMs in production systems. 

Benefits: 

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

#li-remote

Team Description

Ad Safety is a growing team focusing on user safety and advertiser trust by building a robust, automated ecosystem that prioritizes Brand Suitability and Ads Integrity. This is achieved by deploying highly accurate automated ad review systems that vet content before it goes live, coupled with advanced brand safety classifications and controls that give brands granular agency over their ad adjacency along with ensuring Reddit standards are adhered to. By further integrating with trusted third-party verification partners, the platform not only solidifies confidence in its ad effectiveness but also creates a transparent, scalable environment designed to unlock significant revenue growth.

The team is expanding its Fraud counter-measures by consolidating the identification and enforcement of deceptive ads (Malware, Phishing, Scams) and Billing fraud into a centralized platform. Collecting signals across multiple surfaces, in addition to third party vendor integration, will allow for more effective measures to analyze coordinated efforts of bad actors and pre-emptive detection of malignant intent. 

Role Description

Reporting to the Ad Safety Engineering Manager, the person in this role will be the primary technical driver for the new Fraud detection system, working closely with Ad Review, Billing, Policy and other Reddit Safety teams to enhance overall systems. You will drive the long term strategy for the platform, setting measurable goals and taking overall ownership of a critical function in the Ads organization. 

This is a high-agency position for an engineer who can navigate ambiguity and take decisive ownership of the platform's technical direction in collaboration with other engineers, teams, and stakeholders. 

This role acts as both a technically adept deep coder and a force multiplier. It is responsible for working cross-functionally to help establish the long-term technical vision for Fraud Detection, ensuring our systems are highly available and capable of scaling with the marketplace. In this role you will lead large-scale projects through the entire software development lifecycle, from concept through implementation until delivery. 

What You’ll Do

• Steer: Work with the team to select, scope, and drive high-leverage projects that accelerate the development of Fraud Detection to help Reddit achieve its ambitious goals.
• Architect: Help define the 2+ year technical roadmap for the platform, translating complex business needs into a clear strategy for highly available and performant backend services.
• Build: Execute on a strategy to create world-class Fraud Detection systems.
• Amplify: Mentor, coach, and collaborate with other technical contributors, fostering a culture of empathetic technical excellence and proactive problem-solving.
• Collaborate: Work together with a variety of cross-functional teams, including Product Management, Policy and Legal, to ensure Fraud Detection meets the needs of all stakeholders.
• Evolve: Learn and improve technical and non-technical abilities, staying up-to-date on trends and best practices in the Fraud Detection space across the industry.

Qualifications

• Experience: 7+ years of software engineering experience, with a track record of leading large-scale technical projects that require cross-team and cross-functional collaboration.
• Backend Expertise: Strong experience in large-scale distributed systems and developing highly scalable and reliable backend services.
• Technical Ability: Expertise in at least one general-purpose programming language (e.g., Go, Python, Scala, Java, or C++) and ability to grow expertise in Python and Go.
• Leadership: Demonstrated ability to disambiguate complex problems, align stakeholders with different priorities, and aggressively prioritize to execute effectively.
• Communication: Excellent communication skills employed to drive toward consensus, navigate disagreements, and influence decisions across the engineering organization.
• Agency: A bias for action. The ability to identify what needs to be done, take the initiative to make it happen without waiting for direction, and finish the swing.

Preferred Qualifications

• Direct experience as a Tech Lead or in a similar function.
• Previous success as part of an Ads team with a user base in the millions.
• Experience in Ads Fraud, Ad review or Ads Brand Safety
• Proven experience designing, building, and operating scalable platforms.
• Expertise in Python and/or Go.
• Prior experience in Fraud/Malicious actors space
• Proven track record of utilizing LLMs in production systems. 

Benefits: 

• 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

#li-remote

Reddit has a flexible first workforce!

The Ads Measurement Org is dedicated to enhancing the efficiency and user-friendliness of our advertising platform. The Measurement Modeling team owns all the Machine Learning solutions for Ads Measurement, including Identity Matching, Identity Graph, Utility Enhancement for Ads Privacy, Modeled Conversion, and new Measurement Modeling Initiative. As critical and complex part, in Identity Modeling, we are building new advanced machine learning solutions, the space resides in intersection of ads stack that interacts with various upstream and downstream systems, it serves critical business needs for monetization and consumer as well, including Measurement & Reporting, Experimentation, Personalization, Delivery, and Safety etc, requires major XFN as well as cross team/org collaborations.

We are looking for an IC5 Staff ML Engineer of Ads Identity Modeling, to define long term direction and drive architecture evolution, be responsible for engineering quality and enforce best practice, lead new exploration and cross-org collaboration in new modeling initiatives, and champion ML/AI innovation to ensure the solutions utilize SOTA ML technology. Our diverse group of engineers, product managers, data scientists, and ads specialists is excited to welcome you on board!

Minimum Qualifications:

• 7+ years of professional software engineering experience, with at least 3+ years focused on ML-driven systems at scale
• Demonstrated experience architecting and building ads measurement modeling solutions leveraging advanced machine learning techniques
• Strong knowledge of various identifiers (cookies, hashed emails, phone numbers, IP addresses, user agents) and their use in identity resolution
• Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries for feature engineering, model training, and inference
• Solid understanding of large-scale data processing, distributed computing, and data infrastructure (e.g., Spark, Kafka, Beam, Flink)
• Proven technical leadership in cross-functional settings, driving architectural decisions and influencing stakeholders (product, data science, privacy, legal)
• Excellent communication, mentoring, and collaboration skills to align teams on a long-term vision for identity resolution

Responsibilities:

• Lead the technical strategy and architecture for our company’s ads identity modeling solutions and other related ads measurement models
• Design and train advanced ML models while ensuring accuracy, scalability, and compliance with privacy requirements, managing trade-offs between complexity, latency, and prediction quality
• Oversee end-to-end ML workflows—from data ingestion and feature engineering to model training, evaluation, and deployment—optimizing for performance and cost
• Partner with cross-functional teams (e.g., product management, data science, platform engineering, privacy, legal) to define the roadmap and set long-term goals
• Establish engineering best practices, code quality standards, and data governance guidelines to ensure maintainability and trustworthiness of the identity graph
• Mentor and coach junior engineers, fostering a culture of innovation, technical excellence, and knowledge sharing across the organization

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 

#LI-AK1

The Ads Foundations organization is responsible for the technical backbone powering Ads Monetization at scale. Within this ecosystem, efficient resource utilization is critical. Our responsibilities include:

• Tech Evolution & Efficiency: Bringing the Ads tech stacks into the future by architecting systems that are not only performant but financially sustainable.
• Cloud Resources & Data Observability: Designing and implementing the "source of truth" for cloud spend. We standardize best practices among vertical teams to make Cloud and Business impact transparent for every product launch.
• Cost of Revenue Engineering: We don't just track costs; we engineer solutions to optimize them. This role is responsible for the tooling and architectural patterns that allow teams to own their PnL, validate cost estimates, and forecast accurately.

We are seeking a Senior Staff Engineer to serve as the Cloud Resources Technical Owner for the Ads Domain. You will be the primary engineering point of contact for the Senior Director in Ads and Cloud Operations/Resources (COR & Opex) stakeholders. You will not just advocate for efficiency, you will architect the systems that make it inevitable.

What You’ll Do

Technical Vision & Strategy

• Define and drive the technical strategy for Cloud Resource management within Ad first, ensuring that cost accountability is built into the architecture of our systems.
• High-Fidelity Investment Modeling: Elevate cloud estimation from guesswork to a rigorous engineering discipline. You will lead the high-quality forecasting of new cloud investments and efficiency projects, designing data-driven models to validate technical ROI before builds happen
• Design and implement a roadmap for Cost Observability 2.0, moving beyond simple reporting to real-time, service/team-level spend attribution and automated anomaly detection.

Engineering & Tooling Leadership

• Design and build internal platforms that programmatically enforce PnL accountability. You will engineer (or collaborate with Core Infrastructure partners) to deliver the dashboards, alerts, and governance tools that every Ads team relies on to manage their cloud footprint.
• Architect automated frameworks for validating cost estimates and forecasting, replacing manual spreadsheets with data-driven software solutions.

Scale & Optimization

• Fight for observability by instrumenting deep telemetry into our cloud infrastructure. You will be hands-on in identifying inefficiencies (e.g., underutilized clusters, uncompressed data flows) and re-architecting critical paths for cost reduction.
• Lead the technical validation of vendor and 3rd-party tool integration, ensuring we extract maximum engineering value from every dollar spent.

Cultural & Technical Stewardship

• Act as a role model for the Ads domain and the wider company. You will set the standard for how engineering teams think about Cost as a Non Functional Requirement, eventually scaling these patterns to other domains.
• Partner with Finance and Engineering leadership to translate Cloud Spend into actionable engineering tasks (e.g., refactor Service X to use Spot instances).

Who You Might Be

• 10+ years of software engineering experience, with a strong focus on public cloud infrastructure (AWS/GCP/Azure) and large-scale distributed systems.
• Engineer-First Mindset: You are comfortable writing code (Go, Python, Java) to solve infrastructure problems. You don't just ask for a report; you build the API that generates it.
• Deep Cloud Expertise: You have mastery over Kubernetes, container orchestration, and cloud-native storage, understanding exactly how architectural choices impact the bottom line.
• Operational Excellence: Proven track record of building observability pipelines (Prometheus, Grafana, Datadog) that drive operational and financial alerts.
• Influential Leader: Skilled at driving clarity in ambiguous spaces. You can convince a Principal Engineer to refactor their service for cost efficiency because you can prove the technical and business value.

Bonus Points

• Experience building custom FinOps tooling or internal developer platforms.
• Background in performance engineering or capacity planning for high-traffic ad tech environments.
• Contributions to open-source projects related to cloud efficiency or observability.

Benefits: 

• 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

#li-remote

Ads Content Understanding (ACU) is Reddit’s core commercial content understanding team for Ads. The team owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for:

• The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources).
• Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics.
• Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations.
• Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs.
• Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams. 

We are looking for a Staff Machine Learning Engineer who will lead the Commercial Content Understanding roadmap for the Monetization org and act as the technical owner for ACU’s signals and ML systems. Roughly 50% of their time should be spent in technical leadership and mentorship (driving designs, standards, cross-team alignment), and 50% in direct hands-on work (modeling, pipelines, and debugging complex production systems). 

Responsibilities:

• Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, acting as de facto tech lead for content understanding and signals: driving design reviews, setting technical standards, and uplifting the team’s modeling and systems craft.
• Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices. 
• Drive operational excellence for ACU’s ML systems by defining SLOs, alerting, and dashboards for key signals (coverage, latency, precision/recall, cost)
• Build and evolve content understanding capabilities for commercial conversations (e.g., reviews vs. recommendations vs. comparisons vs. Q&A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products.
• Lead design and implementation of signals pipelines and produce an ACU signals registry. Partner with platform teams and other content understanding teams to ensure efficient, reliable serving at Reddit scale.
• Drive LLM and modern ML best practices within ACU: define when to prompt, finetune, or distill; design evaluation and safety harnesses; and lead at least one major distillation effort to replace external APIs with in-house models.
• Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable, resilient MLOps pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production.

Required Qualifications:

• 7+ years of relevant MLE experience delivering production ML systems (models + pipelines + serving) at scale, ideally in large-scale content understanding domains, or Ads. 
• Demonstrated Staff-level technical leadership: has driven architecture decisions, standards, and design reviews across multiple teams, and has aligned PMs, DSs, and engineers on shared ML systems or platforms without direct people-management authority.
• Excellent communication skills, with the ability to explain complex technical trade-offs to PMs, DSs, and other engineering teams, especially in ambiguous, cross-team problem spaces like Seekers/Searchers monetization. 
• Strong track record building and shipping NLP / Language models / content understanding models to production (e.g., classifiers, encoders, sequence or session models), with clear business outcomes (e.g., CTR/ROAS uplift, safety improvements). Experience with commercial or intent modeling is a strong plus.
• Practical experience using LLMs in production for labeling, evaluation, or distillation (e.g., LM-as-judge, prompt-based classifiers, LLM-generated labels distilled into smaller models), including managing quality, cost, and latency trade-offs.
• Deep experience with PyTorch, TensorFlow, or similar, and production-quality code in Python (and ideally one statically typed language like Go/Java/C++). Comfortable owning training, evaluation, and deployment code end-to-end.
• Experience designing ML systems and pipelines: offline training, feature pipelines (batch/streaming), online serving, monitoring, and experimentation for high-traffic surfaces.

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 

#LI-Remote

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

Reddit has a flexible first workforce! if you happen to live close to our physical office location 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 from the Netherlands.

We are looking for a skilled backend software engineer to join the Product Catalogs team. Our team builds products and infrastructure that enable retail advertisers to succeed on Reddit. On our team, you’d work projects like:

• Catalog System Scaling - In order to support larger and more sophisticated advertisers, we must scale our system to support millions of products per customer. You’ll have the opportunity to perform load testing, identify bottlenecks, and deploy optimizations to make these customers successful.
• Catalog Management - With millions of products, advertisers need tools to manage those products, identify errors, and build campaigns based on subsets of products.
• Product Enhancement - Leveraging AI, LLMs and Reddit organic data to make our products more appealing to users by showcasing products popular with Redditors, enhancing product image backgrounds with GenAI, and much more!

Technologies used on the team include:

• Languages: Python, Scala, Go
• Frameworks: gRPC, Thrift, Baseplate, Kafka
• Datastores: Postgres, BigQuery, Redis, TiDB
• Tools: Kubernetes, Airflow

Responsibilities:

• Develop, maintain, and scale our product catalogs backend
• Contribute to the development of features to make our product easier to use
• Produce robust and sustainable code and demonstrate proficiency in debugging systems beyond your immediate responsibilities.
• Uphold high-quality standards within the team.

Required Qualifications:

• A Bachelor's degree or equivalent experience in a quantitative or computer science-related field (e.g., mathematics, statistics, economics, finance, computer science)
• 4+ years of full-time backend software engineering experience in a scalable computing environment
• Experience in backend development, with a passion for learning and adapting to new technologies that you lacked prior experience with
• Strong communication and collaboration skills, with the ability to work effectively with diverse stakeholders independently

Nice to Have:

• Prior experience in the ads or ecommerce space

If you're a talented software engineer looking for a new challenge, and you're passionate about building scalable systems and great customer experiences, we encourage you to apply for this exciting opportunity!

What We Offer:

• A dynamic, supportive work environment with a diverse team of engineers and cross-functional partners
• Opportunities for professional growth and development, with a focus on continuous learning and skill-building
• A competitive salary and benefits package, with a focus on work-life balance and employee well-being
• Flexible work arrangements, including remote work options, to support your individual needs and preferences
• The chance to work on high-impact projects that drive real results for our users and advertisers

Benefits:

• 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
• Private Pension plan with Employer-matching
• 100% employer-sponsored group medical plan  
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

Team Description

The Reddit Ads team is poised to innovate and grow rapidly like never before. This is a unique opportunity to join a high-performing team that will shape how we monetize the Reddit platform and help connect Redditors with brands they love. 

The Agency, Partnership, and SMB (Small and Medium Business) teams share a vision to make Reddit a destination for businesses of all sizes. We are building 0->1 products to create a diversified business. You will work closely with multiple teams across the ads platform and beyond to grow all channels of advertiser growth on the platform, including:

• Acquisition: Acquiring and activating new advertisers to Reddit, including lightweight ads experiences in consumer Reddit, 
• Retention: Ensuring advertisers are set up with the best practices to get performance on the platform, owning the advertiser lifecycle, and providing opinionated guidance in-product for advertisers
• Business Management: From permissions and asset sharing for large customers to unlock new lines of business, to how business operate across organic and paid channels on reddit, to how agencies onboard and work with client advertisers
• API: Creating API-first features, building foundational capabilities for both our 1p platform and 3p partners, and increasing integrations and partnerships

Role Description

We are seeking a Senior Staff Engineer to serve as the technical owner across this entire advertiser growth domain. 

In this role, you will be responsible for developing the technical foundation for mission critical product pillars, collaborating across the company to deliver outcomes for the Reddit Ads Business. This role provides an opportunity to partner closely with cross-functional teams such as product, design, marketing, data science, UX and Sales, and ultimately make a large number of businesses of all sizes successful on Reddit. As a technical leader for all of these efforts, you will set the engineering strategy for building iteratively, shipping quickly, testing rigorously, and adding step-change capabilities towards our ambitious goals to grow and diversify our advertiser base. This is a high-agency position for an engineer who can navigate ambiguity and take decisive ownership of the pillar’s technical direction in collaboration with other engineers, teams, and stakeholders. 

What You’ll Do

• Lead: Work across multiple teams to change the shape of Reddit’s business, and solve problems for many different customers, from SMBs to Agencies to API users
• Architect: Help define the 2+ year technical roadmap for the platform, connecting many complex business needs into a clear strategy for the right technical foundation for the org to execute quickly and with rigor.
• Build: Create the future version of the ads manager, business hub, API, and off-platform experiences, bringing ambitious projects from conception to launch and beyond.
• Amplify: Mentor, coach, and collaborate with other technical contributors, fostering a culture of empathetic technical excellence and proactive problem-solving.
• Collaborate: Work together across product surfaces with a variety of cross-functional teams, including Product Management, Design, Data Science, Product Marketing, and Sales.
• Evolve: Learn and improve technical and non-technical abilities, staying up-to-date on trends and best practices in the Ads industry.

Qualifications

• Experience: 7+ years of software engineering experience, with a track record of leading large-scale technical projects that require cross-team and cross-functional collaboration. Familiarity with experimentation, data-informed decision making, hypothesis design, and customer empathy.
• Technical Ability: Expertise in at least one general-purpose programming language (e.g., Go, Python, Scala, Java, or C++) and ability to grow expertise in Python and Go.
• Leadership: Demonstrated ability to disambiguate complex problems, align stakeholders with different priorities, and aggressively prioritize to execute effectively. Strong ability to deliver through others as well as doing hands-on work
• Communication: Excellent communication skills employed to drive toward consensus, navigate disagreements, and influence decisions across the engineering organization.
• Agency: A bias for action. The ability to identify what needs to be done, take the initiative to make it happen without waiting for direction, and finish the swing.

Benefits: 

• 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

#li-remote

At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning.

We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem.

We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit.

If you love working on complex, real-world ML problems at massive scale, this role is for you.

What You’ll Work On

As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including:

• Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities
• Intelligent advertising systems including ranking, bidding, measurement, and optimization
• Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals
• Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems
• Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement

You’ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes.

What You’ll Do

• Design, build, and deploy production-grade machine learning models and systems at scale
• Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Build scalable data and model pipelines with strong reliability, observability, and automated retraining
• Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems. 
• Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
• Improve system performance across latency, throughput, and model quality metrics
• Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment 
• Contribute to technical strategy, architecture, and long-term ML roadmap

Basic Qualifications

• 3-5+ years of experience building, deploying, and operating machine learning systems in production
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
• Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
• Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
• Experience improving measurable metrics through applied machine learning

Preferred Qualifications

• Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems
• Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
• Experience working with real-time systems and low-latency production environments
• Background in feature engineering, model optimization, and production monitoring
• Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
• Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams

• Ads Measurement Modeling 
• Ads Targeting and Retrieval
• Advertiser Optimization
• Ads Marketplace Quality
• Ads Creative Effectiveness
• Ads Foundational Representations
• Ads Content Understanding
• Ads Ranking
• Feed Relevance
• Search and Answers Relevance
• ML Understanding
• Notifications Relevance

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 

At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning.

We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem.

We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit.

If you love working on complex, real-world ML problems at massive scale, this role is for you.

What You’ll Work On

As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including:

• Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities
• Intelligent advertising systems including ranking, bidding, measurement, and optimization
• Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals
• Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems
• Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement

You’ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes.

What You’ll Do

• Design, build, and deploy production-grade machine learning models and systems at scale
• Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Build scalable data and model pipelines with strong reliability, observability, and automated retraining
• Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems. 
• Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
• Improve system performance across latency, throughput, and model quality metrics
• Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment 
• Contribute to technical strategy, architecture, and long-term ML roadmap

Basic Qualifications

• 3-5+ years of experience building, deploying, and operating machine learning systems in production
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
• Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
• Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
• Experience improving measurable metrics through applied machine learning

Preferred Qualifications

• Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems
• Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
• Experience working with real-time systems and low-latency production environments
• Background in feature engineering, model optimization, and production monitoring
• Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
• Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams

• Ads Measurement Modeling 
• Ads Targeting and Retrieval
• Advertiser Optimization
• Ads Marketplace Quality
• Ads Creative Effectiveness
• Ads Foundational Representations
• Ads Content Understanding
• Ads Ranking
• Feed Relevance
• Search and Answers Relevance
• ML Understanding
• Notifications Relevance

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