Senior Machine Learning Engineer - Discovery (ML + ...

About The CompanyScribd is on a mission to spark human curiosity. We create a world of stories and knowledge, democratize the exchange of ideas, and empower collective expertise through our products: Everand, Scribd, and Slideshare. We value bold, authentic collaboration and place emphasis on customer success.We offer Scribd Flex, a flexible work benefit that lets employees choose a daily work style in partnership with their manager. Occasional in-person attendance is required for all Scribd employees, regardless of location.We hire for GRIT, defined as the intersection of passion and perseverance toward long-term goals. The acronym GRIT guides our expectations: Goals, Results, Innovation, and Team collaboration and attitude.The Recommendations TeamThe Recommendations team powers personalized discovery across Scribd’s products. We operate at the intersection of large-scale data, ML, and product innovation, collaborating across brands and platforms to enhance reading, listening, and learning experiences. The team comprises frontend, backend, and ML engineers who partner with product managers, data scientists, and analysts.Prototype 0→1 solutions with product and engineering teams.Build and maintain production-grade ML systems for recommendations, search, and generative AI features.Develop services in Go, Python, and Ruby powering high-traffic pipelines.Run large-scale A/B and multivariate experiments to validate models and features.Transform large, diverse datasets into actionable insights with measurable business impact.Explore and implement generative AI for conversational recommendations, document understanding, and advanced search.About The RoleWe’re seeking a Machine Learning Engineer to design, build, and optimize ML systems that scale to millions of users. You’ll work across the lifecycle—from data ingestion to model training, deployment, and monitoring—to deliver fast, reliable, and cost-efficient pipelines. You’ll contribute to next-generation AI features like doc-chat and ask-AI to expand user interactions with Scribd’s content.Key ResponsibilitiesData Pipelines – Collaborate to build large-scale ingestion, transformation, and validation pipelines on Databricks.Model Development & Deployment – Train, evaluate, and deploy ML models to production using internal platforms and standard frameworks.Experimentation – Design and run A/B and N-way experiments to measure impact.Cross-Functional Collaboration – Partner with product managers, data scientists, and analysts to deliver user-focused solutions.RequirementsMust Have4+ years of post-qualification experience as a professional ML or software engineer with production ML at scale.Proficiency in Python or Go (Scala or Ruby also considered).Experience designing large-scale ML pipelines and distributed systems.Deep experience with distributed data processing (Spark, Databricks, or similar).Strong cloud expertise (AWS, Azure, or GCP) and deployment platforms (ECS, EKS, Lambda).Proven ability to optimize system performance and make informed ML design trade-offs.Experience leading technical projects and mentoring engineers.Bachelor’s or Master’s in Computer Science or equivalent experience.Nice to HaveExperience with embedding-based retrieval, large language models, or advanced recommendation systems.Expertise in experimentation design, causal inference, or ML evaluation methodologies.Why Work With UsHigh-Impact Environment: Contributions power recommendations, search, and AI features used by millions.Cutting-Edge Projects: Tackle ML/AI problems with a forward-thinking team.Collaborative Culture: A culture that values debate, fresh perspectives, and learning.Flexible Workplace: Scribd Flex with in-person collaboration as a pensation & LocationSalary ranges are determined by location and level. In the United States, ranges vary by state and market. This position is eligible for competitive equity and a comprehensive benefits package. Salary specifics for California, other US markets, Canada, and market considerations are provided in our job description.Are you based in a location where Scribd can employ you? Primary residence should be in or near eligible cities in the United States, Canada, or Mexico as listed in the job posting.Benefits, Perks, And WellbeingHealthcare coverage (Medical/Dental/Vision): 100% paid for employees12 weeks paid parental leave; disability plans401k/RSP matching; onboarding stipend for home office setupLearning & Development allowance and programsWellness, WiFi, and other stipends; mental health resourcesFree Scribd product subscriptions; referral bonuses; book benefit; sabbaticalsCompany-wide events, team budgets; vacation, personal days, holidaysVolunteer day and inclusive workplace programsAccess to AI tools for productivity and innovationWant to learn more about life at Scribd? are committed to equal employment opportunity and encourage applicants from diverse backgrounds. For interview accommodations, email . #J-18808-Ljbffr

Created: 2025-10-08