{"id":123824,"url":"https://alion.io/job/reddit-senior-staff-machine-learning-systems-engineer-ads-ml-platform","title":"Senior Staff Machine Learning Systems Engineer, Ads ML Platform","company":{"id":16,"name":"Reddit","domain":"reddit.com","url":"https://alion.io/company/reddit","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":79,"open_postings":25,"ghost_share":0,"stale_share":0.64,"repost_share":0,"time_to_fill_p50_days":68,"computed_at":"2026-10-23T05:54:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States","United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":292500,"max":409500,"currency":"USD","period":"year","gross":null,"usd_annual":409500},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"Databricks","optional":false},{"name":"Flink","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Ray","optional":false},{"name":"Snowflake","optional":false}],"status":"live","first_seen_at":"2026-08-25T18:40:31Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-10-23T18:00:48Z","board_verified":true,"closed_at":null,"days_open":59,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":59},"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 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.\nReddit 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\nAbout Reddit\n Reddit is a community of communities, built on shared interests, passion, and trust. With 100,000+ active communities and 101M+ daily active unique visitors, we’re one of the largest sources of conversation and knowledge on the internet. For more information, visitredditinc.com.\nTeam Overview\nThe Ads ML Platform team builds infrastructure that accelerates high-scale ML systems and tooling for Ads ML, while extending reusable capabilities to broader Reddit ML use cases where appropriate. Our systems help ML engineers move faster across the full development lifecycle: creating features, generating training data, running offline experiments, validating model quality, launching production models, and operating ML systems reliably.\nWe are looking for a Senior Staff Machine Learning Systems Engineer to lead the technical strategy for the end-to-end Ads ML engineer lifecycle. The initial focus will be on the feature development and training iteration loop: making it faster and easier for ML engineers to build features, generate reliable training data, run experiments, and move from idea to validated model improvement. Over time, this scope will expand into serving and online experimentation workflows, creating a more seamless path from offline iteration to production impact.\nThis is a senior technical leadership role for someone who can combine deep systems expertise, production ML experience, architectural judgment, and cross-team influence.\nWhat You’ll Do\nOwn the technical strategy for the end-to-end Ads ML engineer lifecycle, starting with feature development, training data, offline experimentation, and model iteration workflows.\nAlign Ads ML platform priorities with Reddit’s broader ML Platform vision, translating Ads pain points into reusable platform capabilities where appropriate.\nDefine architecture and technical standards for ML feature and training-data systems across batch/streaming computation, backfills, lineage, quality, observability, and online/offline consistency.\nStay close to ML engineers and platform customers to identify high-leverage friction points and improve day-to-day development velocity.\nBuild platform abstractions and workflow automation that make ML development faster, safer, more reliable, and more self-service.\nOver time, extend the platform strategy into serving and online experimentation workflows, creating a more seamless offline-to-online ML development experience.\nPartner across Ads, ML Platform, Data Platform, modeling, product, and engineering teams to clarify ownership, resolve ambiguity, and drive durable execution.\nMentor Staff and senior engineers, raise the architecture and operational bar, and help grow the next generation of technical leaders.\nWho You Might Be\nYou have 8+ years of experience in infrastructure, distributed systems, ML platforms, data platforms, or large-scale backend systems.\nYou have 4+ years building or operating production ML infrastructure, feature platforms, training data systems, experimentation systems, or large-scale data pipelines.\nYou have led broad, ambiguous, multi-team platform initiatives from strategy through adoption.\nYou have built platforms used directly by ML engineers, data scientists, or product teams developing production ML systems.\nYou have deep experience in ML platform, feature platform, training data, experimentation, developer infrastructure, or distributed data infrastructure.\nYou have worked with distributed data and compute systems such as Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, Databricks, or similar technologies.\nYou can balance urgent customer needs with durable long-term architecture and reusable platform patterns.\nYou influence senior engineers and leaders through clear technical reasoning, RFCs, design reviews, decision frameworks, and operating mechanisms.\nYou are excited to shape how production ML systems are built, scaled, and operated, not only how models are trained.\nBenefits:\nComprehensive Healthcare Benefits and Income Replacement Programs\n401k with Employer Match\nGlobal Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support\nFamily Planning Support\nGender-Affirming Care\nMental Health & Coaching Benefits\nFlexible Vacation & Paid Volunteer Time Off\nGenerous Paid Parental Leave \nPay Transparency:\nThis job posting may span more than one career level.\nIn 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/.\nTo 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.\nThe base salary range for this position is:\n$292,500—$409,500 USD\nIn 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.\nDuring 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.\nReddit 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. 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