Senior Machine Learning Engineer

Job Description As a Senior Machine Learning Engineer at IAS you will be part of a team at the center of the company’s innovation strategy and a major contributor to the company’s core products. You will work on challenging technical problems using machine learning applied to multimodal content classification. The types of challenges we solve have attracted people from industry and academia with diverse backgrounds including machine learning, computer science, finance, physics, biology, neuroscience, and economics. 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. The ideal candidate has a track record of delivering deep learning based models at scale, enjoys working with cross‑functional partners from Product and Engineering, delivering solutions within strict timelines, and brings innovative solutions to complex problems with a desire to improve the status quo. What you’ll get to do Scope work and projects in the realm of machine learning focusing on deep learning applications in image / video classification. Work with a variety of data sources to build production‑ready ML models. Apply machine learning to novel problems in online advertising. Collaborate with engineers to integrate solutions within larger engineering workflows. Effectively communicate results from ML / DL models and statistical learnings to a variety of stakeholders within R&D and product organizations. What you’ll need Advanced degree (MSc, PhD or equivalent industrial experience) in a relevant technical field (machine learning, computer science, computer vision, etc.). 5 years of industry experience delivering machine learning systems from ideation to production. Strong programming skills in Python and experience with deep learning frameworks (e.g., PyTorch, TensorFlow). Good experience developing deep neural networks (CNNs, transformers) preferably applied to NLP, computer vision or audio processing. Experience with source‑control workflows and deploying ML models in production (experience with inference frameworks such as TensorRT, ONNX or Triton is a plus). Comfortable manipulating and analyzing complex high‑volume, high‑dimensional data from varying sources. A continuous learner with a strong interest translating theory into practical solutions. Experience distilling product requirements into problem definitions, dealing with ambiguity and competing objectives. Ability to communicate complex quantitative analysis in a clear, precise and actionable manner. What puts you over the top Practical experience with image / video classification, object detection, speech recognition, machine translation, and similar problems. Publication record in deep learning / neural networks or adjacent fields. Experience working with distributed computing tools applied to machine learning (Ray, Horovod) or to data processing and cloud platforms (AWS, GCP). 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. 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 . #J-18808-Ljbffr