Reddit, Inc.

Research Engineer

• Define the 'Reddit Benchmark' evaluation standard: Own the methodology — not just the harness — for rigorously measuring model quality across Safety, Reasoning, representation/retrieval, and Reddit-specific knowledge. Decide what 'Reddit-native' means in measurable terms and set the bar the org trains against.
• Own evaluation reliability and statistical rigor: Establish the science behind trustworthy evals — judge variance, multi-sample scoring, inter-rater/inter-sample agreement, sampling and temperature effects, and calibration of automated judges. You are accountable for whether a benchmark delta is real or noise. Drive the practice of evaluation as a release gate — offline against frozen datasets, and pre-merge in CI/CD — so regressions are caught before endpoints ship.
• Design model-as-a-judge methodology: Own judge selection, prompt design, calibration, and reliability for automated evaluation using frontier external models, enabling rapid, trustworthy iteration cycles.
• Set post-training recipes and strategy: Design SFT recipes (data mixtures, curriculum, ablation strategy) that convert base models into helpful, well-aligned endpoints; partner with engineering to scale them.
• Evaluate base and CPT checkpoints, not just endpoints: Design checkpoint-selection methodology across CPT experiments and LR studies, so we pick the right base before committing post-training compute.
• Drive synthetic data generation strategy: Define and curate high-quality instruction and evaluation sets to improve generalization where human data is scarce.
• Partner with Safety Engineering: Translate high-level safety policy into concrete classification metrics, probe sets, and CI/CD unit tests — including precision/recall at threshold, label-noise handling, and false-positive taxonomy for abuse detection (HHV).
• Diagnose post-training instability: Dive into loss curves and eval logs to identify alignment tax and capability degradation, and recommend the fix.
• Lead research direction: Set technical direction for evaluation and post-training across the team, mentor engineers and scientists, and represent the work internally (and externally where appropriate).

Staff Research Engineer – Post-training & Evaluation

Engineering Manager

• Lead a high-performing team of software and machine learning engineers focused on Shopping Ads targeting, retrieval, ranking, and engagement models
• Drive technical execution for Dynamic Product Ads and Product Listing Ads across ads targeting, candidate retrieval, ranking integrations, model features, and engagement optimization
• Act as a hands-on technical leader by contributing to architecture reviews, technical design, debugging complex production issues, and guiding implementation decisions
• Partner closely with ML Platform, Ads Serving, Product, Data Science, Measurement, and Infrastructure teams to define roadmaps and deliver advertiser impact
• Improve scalability, latency, reliability, relevance, experimentation quality, and operational excellence across Shopping Ads systems
• Drive simplification and platformization efforts that improve developer velocity and reduce operational complexity
• Establish strong engineering practices around system design, experimentation, code quality, observability, and production ownership
• Mentor and develop engineers and technical leads while fostering a culture of technical rigor, accountability, speed, and pragmatic execution
• Identify architectural bottlenecks, technical debt, and scaling risks, and proactively drive solutions across organizational boundaries
• Stay current with industry trends in commerce advertising, recommendation systems, retrieval and ranking architectures, and Shopping Ads optimization

Senior Engineering Manager, Shopping Ads

Frontend Engineer

• Build performant, mobile-optimized ad growth experiences on ads.reddit.com and on partner platforms such as Shopify and WooCommerce
• Work closely with product, design, and engineering partners to turn business goals and product requirements into clear technical plans and high-quality user experiences
• Break down ambiguous problems into iterative, shippable milestones and make steady progress across multiple priorities
• Communicate status, tradeoffs, risks, and blockers clearly and early, and ask for help when needed to keep work moving
• Engage in the full development cycle: design, develop, test, experiment, analyze, and deploy
• Contribute to a strong team culture through thoughtful code reviews, feedback, and day-to-day collaboration
• Ramp quickly on the team’s domain, systems, and development workflows so you can make meaningful contributions early

Frontend Engineer, Ads Growth

Full-stack Engineer

• Design, build, and ship high-quality features across the stack, with a focus on creating reusable, maintainable UI components and polished frontends that scale with the platform
• Contribute to backend systems to deliver cohesive, end-to-end product experiences
• Define and enforce clean API boundaries between frontend and backend systems
• Collaborate with teammates to build a platform that supports:
• Orchestrating complex deployment workflows
• Progressive rollouts across clusters and regions
• Automated rollback of failed deployments
• Observability into deployment health and performance
• Translate complex infrastructure technologies and concepts (e.g., Kubernetes, Argo Rollouts, deployment policies) into intuitive, user-friendly interfaces
• Engage directly with engineers across Reddit—conducting user interviews, gathering feedback, and deeply understanding developer workflows—to shape an opinionated “paved path” for releases
• Raise the bar for full-stack engineering across the team through code reviews, mentorship, and knowledge sharing
• Participate in the team’s on-call rotation and contribute to the reliability of our platform
• Continuously grow your technical and non-technical skills

Senior Software Engineer – Full Stack, Internal Tooling, Build and Deployment Platform

• Lead a high-impact team of 13 engineers enabling automated AI training and human-in-the-loop workflows at the core of Reddit’s safety strategy
• Own the user-facing tools used by moderators to define and automatically enforce the rules in their communities
• Own the centralized platform used by admins to train AI models for content and behavior detection at scale, process reports and appeals, and investigate suspicious users and activity
• Partner cross-functionally with Product, Data Science, ML, and Operations to define and execute an AI-first platform strategy capable of supporting a 10x surge in scale while slashing incident response from days to seconds

Engineering Manager, Safety

• As the Engineering Manager of the Ads Advanced Signals Team at Reddit, you'll lead the team responsible for the APIs, integrations, and tooling that power both inbound and outbound signals for Reddit Ads, which includes helping advertisers
• Your primary mission will be to scale and evolve the APIs, integrations, and tooling that power Reddit’s off-platform signals ecosystem. This includes both collecting high-quality inbound signals and delivering outbound data products that advertisers and partners use to measure and optimize performance.
• You will own the execution of your team’s roadmap and be accountable for consistent, predictable delivery. You will prioritize both planned projects and emergent asks.
• You will help your engineers identify career goals and create development plans to achieve them.
• You will work with your team to develop processes and tooling that constantly improve the quality of our products and systems, ensuring that they meet product requirements, customer needs, and SLAs.
• You will serve as a thought partner to product and upper management to ensure your team’s plans align with company goals.

Engineering Manager, Advanced Signals

Technical Product Manager

• Define the Vision: Shape the long-term strategy and roadmap for Reddit’s Ads ML platform, ensuring we are adopting cutting-edge technologies (including Generative AI and LLM workflows) to stay ahead of the curve.
• Accelerate Velocity: Build products and tooling that dramatically reduce friction for Machine Learning Engineers (MLEs) and Data Scientists, enabling them to train, deploy, and iterate on models faster than ever.
• Cross-Functional Leadership: Partner deeply with Engineering, Data Science, and Ads Product teams to understand their constraints, prioritize platform initiatives, and deliver scalable infrastructure.
• Drive Execution and Adoption: Own key performance indicators (KPIs) around platform reliability, latency, cost-efficiency, usage metrics, and developer productivity.
• Stay Cutting-Edge: Keep your finger on the pulse of the broader ML ecosystem. Read the latest research papers, understand emerging architectures, and determine how they can be practically applied to Reddit’s Ads ML platform.
• Distill pain points, translate to requirements: Conduct regular user research with MLEs in Ranking, Creative Effectiveness and Content Understanding to convert pain points (e.g., slow backfills, limited training speed, no way to quickly share features across models) into precise product requirements. Validate the needs and ensure they are tied into a broader vision for the org.

Staff Technical Product Manager, Ads ML Platform

Data Scientist

• Serve as the technical authority on relevance metrics and evaluation methodology across Consumer, setting standards for how we measure the quality of feeds, search results, and recommendations in a complex, community-driven environment
• Develop metrics frameworks and offline evaluation approaches for ranking and recommendation systems, including proxy metrics that reliably predict long-term outcomes like retention, community health, and user satisfaction
• Design and analyze experiments for relevance features, accounting for challenges unique to networked platforms such as spillover effects between communities, interference between contributors and consumers, and long-run impacts of ranking changes on content supply
• Identify opportunities where improved measurement and analysis can unlock product insights that were previously unmeasurable or ambiguous, particularly around content quality, search intent understanding, and personalization effectiveness
• Partner deeply with ML engineers and product teams to translate model performance metrics into user-facing impact
• Influence the long-term product strategy for Feeds and Search by synthesizing insights from experimentation, observational analysis, and metric deep-dives into clear, actionable recommendations for senior leadership
• Mentor and elevate other data scientists across the organization on relevance evaluation, experimentation best practices for ranking systems, causal reasoning, and statistical rigor
• Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader relevance, recommendation systems, and experimentation community

Senior Staff Data Scientist – Consumer Relevance

• Serve as the technical authority on experimentation methodology across Consumer, setting standards for design, analysis, and interpretation of experiments in a complex, networked environment
• Tackle the hardest experimentation problems at Reddit, including spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation
• Develop and advance methods for causal inference in settings where standard randomization assumptions are violated, such as cluster-randomized designs, switchback experiments, and synthetic control approaches
• Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects, ensuring product teams can measure true causal impact rather than biased local estimates
• Identify opportunities where improved experimentation methodology can unlock product insights that were previously unmeasurable or ambiguous
• Build and scale self-serve experimentation tools, platforms, and best-practice documentation that increase experimentation velocity and literacy across product, engineering, and design teams
• Influence the long-term product strategy by driving learning through well-designed experiments and translating experimental results into clear, actionable recommendations for senior leadership
• Mentor and elevate other data scientists across the organization on experimentation best practices, causal reasoning, and statistical rigor
• Publish and share methodological advances internally and, where appropriate, externally to contribute to the broader experimentation and causal inference community

Senior Staff Data Scientist – Consumer Experimentation

• Work with product managers to design and implement Ads products.
• Collaborate closely with the platform and data teams while building new features.
• Lead the processes needed to improve operational stability, including improving code quality, delivering dashboards and data visualizations.
• Build extensible components that would align with the product objectives.
• Support day to day project management tasks including communicating project updates, managing project timelines and overseeing project execution.

Senior Software Engineer, Ads

Software Engineer

Affiliate Manager

• Lead execution of core Experience programs:
• ERGs and ERIGs (day-to-day operations and support)
• Reddit Odyssey (aka new hire onboarding)
• Snoo Community Funds (intake, tracking, and distribution)
• Speaker Series
• Year-end programming
• Community-driven initiatives and events
• Act as the primary partner for employee-led initiatives:
• Support ERG leaders and community organizers with structure, tools, and guidance
• Enable employee-driven subreddits and grassroots programming
• Help scale participation and engagement across regions and teams
• Help own the operational backbone of Experience programming:
• Manage timelines, communications, and cross-functional coordination
• Partner with vendors, internal stakeholders, and local teams
• Track budgets and ensure programs are delivered within scope
• Support measurement and iteration of programs:
• Track participation, engagement, and feedback
• Identify opportunities to improve programs and processes
• Share insights with Experience leadership to inform strategy
• Work closely with the Lead, Employee Experience Content &amp; Community:
• Translate strategic direction into actionable plans
• Ensure alignment with content, design, and overall Experience standards
• Collaborate across Comms, People, and other partner teams

Experience Partner, Programs

• Design, develop, and maintain user facing product features while ensuring performance, security, and scalability of our systems.
• Work collaboratively with product managers, designers, data scientists and other engineers to deliver high-quality products.
• Contribute to the full development cycle: technical design, development, test, experimentation, analysis, and launch. You’ll be reviewing code and design docs, giving feedback on product specs and mocks.
• Set and define standards that improve developer workflows, recommend best practices, and help coach and mentor engineers on the team to further their professional development.
• Continuously learn and improve your technical and non-technical abilities.

Staff Research Engineer – Post-training & Evaluation

Senior Engineering Manager, Shopping Ads

Frontend Engineer, Ads Growth

Senior Software Engineer – Full Stack, Internal Tooling, Build and Deployment Platform

Engineering Manager, Safety

Engineering Manager, Advanced Signals

Staff Technical Product Manager, Ads ML Platform

Senior Staff Data Scientist – Consumer Relevance

Senior Staff Data Scientist – Consumer Experimentation

Senior Software Engineer, Ads

Senior Staff Data Scientist – Consumer Relevance

Senior Staff Data Scientist – Consumer Experimentation

Software Engineer

Experience Partner, Programs

Senior Frontend Engineer, Community Builders