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Senior Machine Learning Engineer
1 hour ago
Join to apply for the Senior Machine Learning Engineer - Discovery (ML + Backend Engineering) role at Scribd, Inc. About The Company At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. We create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our four products: Everand, Scribd, Slideshare, and Fable. We support a culture where employees can be real and bold, debate and commit, and prioritize the customer. We believe in balancing individual flexibility and community connections through Scribd Flex. Occasional in‑person attendance is required for all employees. We hire for “GRIT” – Goals, Results, Innovation, Team. We look for someone who can set and achieve goals, deliver results, contribute innovative ideas, and positively influence the team. About The Recommendations Team The Recommendations team powers personalized discovery across Scribd’s products, delivering relevant and engaging suggestions to millions of users. The team is a blend of frontend, backend, and ML engineers partnering with product managers, data scientists, and analysts. Key Responsibilities Data Pipelines – Collaborate with engineering and analytics teams to build large‑scale ingestion, transformation, and validation pipelines on Databricks. Model Development & Deployment – Train, evaluate, and deploy ML models (including generative models) to production using Scribd’s internal platform and industry‑standard frameworks. Experimentation – Design and run A/B and N‑way experiments to measure the impact of model and feature changes. Cross‑Functional Collaboration – Partner with product managers, data scientists, and analysts to identify opportunities, define requirements, and deliver solutions that solve real user problems. Requirements Must Have 4+ years of professional ML or software engineering experience, with a proven track record of delivering production ML systems at scale. Proficiency in at least one key programming language (preferably Python or Golang; Scala or Ruby also considered). Expertise in designing and architecting large‑scale ML pipelines and distributed systems. Deep experience with distributed data processing frameworks (Spark, Databricks, or similar). Strong cloud expertise (AWS, Azure, or GCP) and experience with deployment platforms (ECS, EKS, Lambda). Proven ability to optimize system performance and make informed trade‑offs in ML model and system design. Experience leading technical projects and mentoring engineers. Bachelor’s or Master’s degree in Computer Science or equivalent professional experience. Nice to Have Experience with embedding‑based retrieval, large language models, advanced recommendation or ranking systems. Expertise in experimentation design, causal inference, or ML evaluation methodologies. Why Work With Us High‑Impact Environment: Your contributions power recommendations, search, and next‑generation AI features used by millions of readers, learners, and listeners worldwide. Cutting‑Edge Projects: Tackle challenging ML and AI problems with a forward‑thinking team, building novel generative features on top of Scribd’s massive and unique dataset. Collaborative Culture: Join a culture that values debate, fresh perspectives, and a willingness to learn from each other. Flexible Workplace: Benefit from Scribd Flex, which offers autonomy in choosing your daily work style, while still prioritizing in‑person collaboration. Compensation and Benefits In the United States, the expected salary range for this role is $129,500‑$220,000. In California, the range is $157,500‑$230,000. In Canada, the range is CAD 165,000‑218,000. The position also offers equity, a comprehensive benefits package, and a competitive benefits program. Location Eligibility Employees must have their primary residence in or near one of the following cities: United States – Atlanta, Austin, Boston, Dallas, Denver, Chicago, Houston, Jacksonville, Los Angeles, Miami, New York City, Phoenix, Portland, Sacramento, Salt Lake City, San Diego, San Francisco, Seattle, Washington D.C. Canada – Ottawa, Toronto, Vancouver Mexico – Mexico City. Benefits, Perks, and Wellbeing Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees 12 weeks paid parental leave Short‑term/long‑term disability plans 401k/RSP matching Onboarding stipend for home office peripherals + accessories Learning & Development allowance and programs Quarterly stipend for Wellness, WiFi, etc. Mental Health support & resources Free subscription to Scribd’s suite of products Referral bonuses Book benefit Sabbaticals Company-wide events Team engagement budgets Vacation & Personal Days Paid holidays (including winter break) Flexible sick time Volunteer day Company-wide Employee Resource Groups and programs that foster an inclusive workplace. Access to AI Tools: free access to best‑in‑class AI tools. Equal Opportunity Employment We want our interview process to be accessible to everyone. Please inform us of any reasonable adjustments we can make to accommodate your needs at any point in the interview process by emailing Scribd is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply. #J-18808-Ljbffr
