Senior Machine Learning Engineer

Key Skills

Aartificial intelligence, Algorithms, Analytical and Problem solving, Caffe, Continuous Integration & Continuous Delivery - CI/CD, Design, Machine learning techniques, Mentoring, PyTorch, Scikit-learn, SparkML, TensorFlow

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 Senior Machine Learning Engineer on the Data Sciences 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 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 be responsible for overseeing a sophisticated suite of data science systems making large scale business predictions in advertising inventory across open web, social networks, video/CTV, and mobile apps. As part of the data science group at IAS, you will push the boundaries of applications of machine learning (ML) and deliver best-in-class solutions for our clients. Innovation is at the heart of our competitive advantage, and innovation starts with people and culture. You will manage a group of data scientists and cultivate innovation in their work, developing high performing talent, ultimately producing a lasting impact on the IAS business.

The types of challenges we solve have attracted people from industry and academia with diverse backgrounds, ranging from ML, mathematics, physics, biology, neuroscience, and computer science to finance 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.

What you’ll get to do:

• Contribute to the system design for our AI/ML-based services.
• Design and develop testing and monitoring tools for ML models.
• Design and build data pipelines (from storage to monitoring/telemetry).
• Design, develop and support our CI/CD pipeline for AI/ML-based services.
• Provide and maintain experimenting tools for our ML scientists
• Evaluate the technical tradeoffs of every decision
• Perform code reviews and ensure exceptional code quality
• Build robust, lasting, and scalable products Iterate quickly without compromising quality

You should apply if you have most of this experience:

• PhD/Master’s degree in technical field such as computer science, mathematics, statistics or equivalent years of experience
• 3+ years machine learning experience in industry
• Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks
• Experience working with machine learning, ranking infrastructures, and system design
• Strong understanding of machine learning approaches and algorithms
• Able to prioritize duties and work well on your own
• Ability to work with both internal and external partners
• Skilled at solving open ambiguous problems
• Strong collaboration and mentorship skills

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.