Scribd-posted 3 months ago
$120,000 - $228,000/Yr
Full-time • Mid Level
251-500 employees

We’re looking for a Machine Learning Engineer who will design, build, and optimize ML systems that scale to millions of users. You’ll work across the entire lifecycle — from data ingestion to model training, deployment, and monitoring — with a focus on creating fast, reliable, and cost-efficient pipelines. You’ll also play a key role in delivering next-generation AI features like doc-chat and ask-AI that expand how users interact with Scribd’s content.

  • Collaborate with engineering and analytics teams to build large-scale ingestion, transformation, and validation pipelines on Databricks.
  • Train, evaluate, and deploy ML models (including generative models) to production using Scribd’s internal platform and industry-standard frameworks.
  • Design and run A/B and N-way experiments to measure the impact of model and feature changes.
  • Partner with product managers, data scientists, and analysts to identify opportunities, define requirements, and deliver solutions that solve real user problems.
  • 4+ years of post qualification experience as a professional ML or software engineer, 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.
  • Experience with embedding-based retrieval, large language models, advanced recommendation or ranking systems.
  • Expertise in experimentation design, causal inference, or ML evaluation methodologies.
  • 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
  • Learning & Development programs
  • Quarterly stipend for Wellness, WiFi, etc.
  • Mental Health support & resources
  • Free subscription to the Scribd Inc. suite of products
  • Referral Bonuses
  • Book Benefit
  • Sabbaticals
  • Company-wide events
  • Team engagement budgets
  • Vacation & Personal Days
  • Paid Holidays (+ winter break)
  • Flexible Sick Time
  • Volunteer Day
  • Company-wide Employee Resource Groups and programs that foster an inclusive and diverse workplace.
  • Access to AI Tools: We provide free access to best-in-class AI tools, empowering you to boost productivity, streamline workflows, and accelerate bold innovation.
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