Scribd, Inc.
Overview
Join to apply for the
Senior Machine Learning Engineer
role at
Scribd, Inc. About the company: Scribd’s mission is to spark human curiosity by democratizing the exchange of ideas and information through its products: Everand, Scribd, and Slideshare. Role Overview
We are seeking a Senior Machine Learning Engineer to lead the design, architecture, and optimization of high-impact ML systems that serve millions of users in near real time. In this role, you will: Drive technical direction for both platform and product-facing ML initiatives. Lead complex, cross-team projects from conception to production deployment. Mentor other engineers and establish best practices for building scalable, reliable ML systems. Influence the roadmap and architecture of our ML Platform. Tech Stack
Our ML team uses a range of technologies to build and operate large-scale ML systems. Toolkit typically includes: Languages: Python, Golang, Scala, Ruby on Rails Orchestration & Pipelines: Airflow, Databricks, Spark ML & AI: AWS Sagemaker, embedding-based retrieval (Weaviate), feature store, model registry, model serving platforms, LLM providers APIs & Integration: HTTP APIs, gRPC Infrastructure & Cloud: AWS (Lambda, ECS, EKS, SQS, ElastiCache, CloudWatch), Datadog, Terraform Key Responsibilities
Lead design and architecture of ML pipelines from data ingestion and feature engineering to model training, deployment, and monitoring. Own the technical direction of core ML Platform components such as the feature store, model registry, and embedding-based retrieval systems. Collaborate with product software engineers to deliver ML models that enhance recommendations, personalization, and generative AI features. Guide experimentation strategy, A/B testing design, and performance analysis to inform production decisions. Optimize systems for performance, scalability, and reliability across massive datasets and high-throughput services. Establish and uphold engineering best practices, including code quality, system design reviews, and operational excellence. Mentor and coach ML engineers, fostering technical growth and collaboration across the team. Work with leadership to align technical initiatives with long-term ML strategy. Requirements
Must Have
6+ years of 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. Nice to Have
Experience with embedding-based retrieval, large language models, advanced recommendation or ranking systems. Experience building or leading development of feature stores, model serving & monitoring platforms, and experimentation systems. Expertise in experimentation design, causal inference, or ML evaluation methodologies. Contributions to open-source ML/AI tooling or infrastructure. Benefits & Working at Scribd
We offer a comprehensive benefits package and opportunities for growth. This section includes information on salary ranges, location policies, and wellbeing perks, and may include details on equity and the interview process. The salary ranges are stated for indicative purposes and vary by location and level. Working at Scribd, you must be based in locations where Scribd can employ you. Primary residence should be in or near listed cities in the United States, Canada, or Mexico, with occasional in-person collaboration requirements. We are committed to equal employment opportunity and encourage applicants from all backgrounds. For adjustments to the interview process or accommodations, please email accommodations@scribd.com. This company is an equal opportunity employer and prohibits discrimination based on protected characteristics. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries: Software Development Referrals increase your chances of interviewing at Scribd, Inc. by 2x Get notified about new Senior Machine Learning Engineer jobs in Dallas, TX.
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Join to apply for the
Senior Machine Learning Engineer
role at
Scribd, Inc. About the company: Scribd’s mission is to spark human curiosity by democratizing the exchange of ideas and information through its products: Everand, Scribd, and Slideshare. Role Overview
We are seeking a Senior Machine Learning Engineer to lead the design, architecture, and optimization of high-impact ML systems that serve millions of users in near real time. In this role, you will: Drive technical direction for both platform and product-facing ML initiatives. Lead complex, cross-team projects from conception to production deployment. Mentor other engineers and establish best practices for building scalable, reliable ML systems. Influence the roadmap and architecture of our ML Platform. Tech Stack
Our ML team uses a range of technologies to build and operate large-scale ML systems. Toolkit typically includes: Languages: Python, Golang, Scala, Ruby on Rails Orchestration & Pipelines: Airflow, Databricks, Spark ML & AI: AWS Sagemaker, embedding-based retrieval (Weaviate), feature store, model registry, model serving platforms, LLM providers APIs & Integration: HTTP APIs, gRPC Infrastructure & Cloud: AWS (Lambda, ECS, EKS, SQS, ElastiCache, CloudWatch), Datadog, Terraform Key Responsibilities
Lead design and architecture of ML pipelines from data ingestion and feature engineering to model training, deployment, and monitoring. Own the technical direction of core ML Platform components such as the feature store, model registry, and embedding-based retrieval systems. Collaborate with product software engineers to deliver ML models that enhance recommendations, personalization, and generative AI features. Guide experimentation strategy, A/B testing design, and performance analysis to inform production decisions. Optimize systems for performance, scalability, and reliability across massive datasets and high-throughput services. Establish and uphold engineering best practices, including code quality, system design reviews, and operational excellence. Mentor and coach ML engineers, fostering technical growth and collaboration across the team. Work with leadership to align technical initiatives with long-term ML strategy. Requirements
Must Have
6+ years of 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. Nice to Have
Experience with embedding-based retrieval, large language models, advanced recommendation or ranking systems. Experience building or leading development of feature stores, model serving & monitoring platforms, and experimentation systems. Expertise in experimentation design, causal inference, or ML evaluation methodologies. Contributions to open-source ML/AI tooling or infrastructure. Benefits & Working at Scribd
We offer a comprehensive benefits package and opportunities for growth. This section includes information on salary ranges, location policies, and wellbeing perks, and may include details on equity and the interview process. The salary ranges are stated for indicative purposes and vary by location and level. Working at Scribd, you must be based in locations where Scribd can employ you. Primary residence should be in or near listed cities in the United States, Canada, or Mexico, with occasional in-person collaboration requirements. We are committed to equal employment opportunity and encourage applicants from all backgrounds. For adjustments to the interview process or accommodations, please email accommodations@scribd.com. This company is an equal opportunity employer and prohibits discrimination based on protected characteristics. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries: Software Development Referrals increase your chances of interviewing at Scribd, Inc. by 2x Get notified about new Senior Machine Learning Engineer jobs in Dallas, TX.
#J-18808-Ljbffr