Staff Machine Learning Engineer

Integralads; New York (NY); On-site; USD 135,000 - 232,000; Full time

Benefits offered by this job

Health insurance

401k with employer matching

Annual bonus

Job summary

Integral Ad Science is seeking a Staff Machine Learning Engineer to lead architectural design for core AI/ML services and oversee large-scale, low-latency model training platforms. You will collaborate with product and engineering leaders to translate business needs into scalable ML solutions.

You will mentor other engineers, set coding standards, and drive end-to-end ML deployment from research to production, ensuring robust CI/CD for AI services.

Qualifications

• PhD/Master’s degree in a technical field such as computer science, mathematics, statistics, or equivalent years of experience.
• 7+ years of machine learning experience in industry at Lead/Principal/Staff level.
• Deep expertise in designing complex ML systems, ranking infrastructures, and data pipelines for massive throughput.
• Extensive production-grade experience with ML frameworks (PyTorch, JAX, TensorFlow).
• Strong production coding skills in Python, Go, Java, or C++.
• Proven ability to drive large ambiguous problems to technical resolutions and mentor teams.

Responsibilities

• Drive architectural vision and design for core AI/ML services.
• Lead complex initiatives from inception to deployment.
• Design large-scale deep learning infrastructure for distributed model training.
• Collaborate with product, engineering, and leadership to align ML with business goals.
• Mentor senior and mid-level engineers and data scientists.

Skills

Lead ML experience

System design

ML frameworks

Production coding

Ambiguity execution

Mentorship

Education

PhD/Master's in CS/math/stat

Tools

PyTorch

JAX

TensorFlow

Job description

Job Description:

Integral Ad Science (IAS) is a global technology and data company that builds verification, optimization, and analytics solutions for the advertising industry, and we’re looking for a Staff Machine Learning Engineer on the Data Science Team. If you are excited by technology that has the power to handle hundreds of thousands of transactions per second; collect tens of billions of events each day; and evaluate thousands of data points in real-time all while responding in just a few milliseconds, then IAS is the place for you!

As a Staff Machine Learning Engineer at IAS, you will be part of a team that is at the center of innovation for the company and a major contributor to our core products. You will oversee a sophisticated suite of data science systems making large-scale business predictions across the open web, social networks, video, and mobile apps.

At the Staff level, you are expected to be a technical pillar for the organization. You will take ownership of open, highly ambiguous business problems and translate them into scalable ML architectures. You will define technical roadmaps, set the standard for ML engineering practices, and push the boundaries of applied machine learning to deliver best-in-class solutions for our clients. Innovation is at the heart of our competitive advantage, and you will cultivate it by mentoring talent and raising the technical bar across multiple teams. The types of challenges we solve have attracted people from industry and academia with diverse backgrounds. We’re passionate about maintaining an open and collaborative environment, where team members bring their own unique style of thinking and tools to the table.

What you’ll get to do:

• Technical Leadership & Vision: Drive the architectural vision and system design for our core AI/ML-based services.


• Act as the technical lead for complex, multi-quarter initiatives from inception to global deployment.


• Architect at Scale: Design and build large-scale deep learning infrastructure and platforms for distributed model training, ensuring low-latency and high-availability at enterprise scale.


• Cross-Functional Influence: Partner with Product Management, Core Engineering, and executive stakeholders to align ML capabilities with business strategy.


• Translate abstract product requirements into concrete technical designs.


• Act as a Multiplier: Mentor and guide senior and mid-level data scientists and engineers.


• Establish standard methodologies, define code quality expectations, and lead architecture design reviews.


• Infrastructure Mastery: Work with large-scale AI training infra components (accelerators, network fabrics, CUDA, NCCL, RDMA) and big data ecosystems (Databricks, Spark, Kubernetes, Kafka, Prometheus).


• End-to-End Ownership: Design, develop, and support robust CI/CD pipelines for AI/ML services, ensuring models transition smoothly from research into reliable production endpoints.

You should apply if you have most of this experience:

• PhD/Master’s degree in a technical field such as computer science, mathematics, statistics, or equivalent years of experience.


• 7+ years of machine learning experience in industry, with a proven track record of operating at a Lead, Principal, or Staff level.


• System Design & Architecture: Deep expertise in designing complex machine learning systems, ranking infrastructures, and data pipelines that handle massive throughput.


• ML Frameworks: Extensive, production-hardened experience working with frameworks such as PyT orch, JAX, or T ensorFlow.


• Production Coding: Strong, production-grade programming skills in Python, Go, Java, or C++, along with a deep understanding of software design principles and algorithms.


• Ambiguity & Execution: Proven ability to thrive in ambiguity, take large unstructured problems, and independently drive them to successful technical resolutions.


• Mentorship: A strong history of collaborating with, elevating, and mentoring engineering talent

IAS Pay Transparency:

The annualized base salary ranges for the primary location, and any additional locations are listed below. Our pay ranges are based on the work location. As part of IAS compensation package, we offer a comprehensive benefits package that includes paid time off, health insurance (medical, dental, vision) as well as PPO, HSA and FSA options and 401k with employer matching contributions. All full-time employee roles include competitive compensation and are eligible for an annual bonus and/or other incentive plans. Each candidate’s compensation package is based on multiple factors, but not limited to, geography, experience, skills, job duties, and business need.

Primary Location:

US - New York, NY

Primary Location Base Pay Range:

$135,100.00 - $231,600.00 Annual

Additional Locations:

US - Chicago, IL, US - San Francisco, CA

Additional Locations Pay Range:

119,000.00 - 204,000.00 USD Annual

About Integral Ad Science:

Integral Ad Science (IAS) is a leading global media measurement and optimization platform that delivers the industry’s most actionable data to drive superior results for the world’s largest advertisers, publishers, and media platforms. IAS’s software provides comprehensive and enriched data that ensures ads are seen by real people in safe and suitable environments, while improving return on ad spend for advertisers and yield for publishers. Our mission is to be the global benchmark for trust and transparency in digital media quality. For more information, visit integralads.com.

Equal Opportunity Employer:

IAS is an equal opportunity employer, committed to our diversity and inclusiveness. We will consider all qualified applicants without regard to race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability or age. We strongly encourage women, people of color, members of the LGBTQIA community, people with disabilities and veterans to apply.

California Applicant Pre-Collection Notice:

We collect personal information (PI) from you in connection with your application for employment or engagement with IAS, including the following categories of PI: identifiers, personal records, commercial information, professional or employment or engagement information, non-public education records, and inferences drawn from your PI. We collect your PI for our purposes, including performing services and operations related to your potential employment or engagement. For additional details or if you have questions, contact us at [e-mail].