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Integral Ad Science

Digital ad verification, optimization, analytics platform

Staff Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-time$119k - $231.6k /yrHybrid

About the Job

Requirements

  • A PhD or Master’s degree in a technical field such as computer science, mathematics, or statistics, or equivalent years of experience.
  • At least 7 years of machine learning experience in industry, with a proven track record of operating at a Lead, Principal, or Staff level.
  • Deep expertise in designing complex machine learning systems, ranking infrastructures, and data pipelines that handle massive throughput.
  • Extensive, production-hardened experience with machine learning frameworks such as PyTorch, JAX, or TensorFlow.
  • Strong production-grade programming skills in Python, Go, Java, or C++, along with a deep understanding of software design principles and algorithms.
  • Proven ability to thrive in ambiguity, take large unstructured problems, and independently drive them to successful technical resolutions.
  • A strong history of collaborating with, elevating, and mentoring engineering talent.

Responsibilities

  • Drive the architectural vision and system design for core AI/ML-based services.
  • Act as the technical lead for complex, multi-quarter initiatives from inception to global deployment.
  • Design and build large-scale deep learning infrastructure and platforms for distributed model training, ensuring low latency and high availability at enterprise scale.
  • Partner with Product Management, Core Engineering, and executive stakeholders to align machine learning capabilities with business strategy.
  • Translate abstract product requirements into concrete technical designs.
  • Mentor and guide senior and mid-level data scientists and engineers.
  • Establish standard methodologies, define code quality expectations, and lead architecture design reviews.
  • Work with large-scale AI training infrastructure components, including accelerators, network fabrics, CUDA, NCCL, and RDMA, and big data ecosystems including Databricks, Spark, Kubernetes, Kafka, and Prometheus.
  • Design, develop, and support robust CI/CD pipelines for AI/ML services, ensuring models transition smoothly from research into reliable production endpoints.

About the Company

Integral Ad Science

Digital ad verification, optimization, analytics platform

Preparing company summary.

Company size
1,001-5,000
Company stage
IPO
Headquarters
New York City, New York
Founded
2009

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