Chicago, United States; New York, US; San Francisco, United States
Full job description
Integral Ad Science (IAS) is hiring a Staff Machine Learning Engineer for their Data Science Team. The role involves leading the design and architecture of large-scale AI/ML systems handling high throughput and low latency. Responsibilities include driving technical vision, leading multi-quarter projects, building deep learning infrastructure, collaborating cross-functionally, mentoring engineers, and managing CI/CD pipelines for AI/ML services. Candidates should have a PhD or Master’s in a technical field or equivalent experience, 7+ years in machine learning with leadership experience, strong system design skills, production experience with ML frameworks (PyTorch, JAX, TensorFlow), and programming skills in Python, Go, Java, or C++. Benefits include paid time off, health insurance, 401k with matching, competitive salary, and bonuses. Locations include New York, NY; Chicago, IL; and San Francisco, CA.
What you'll do
Drive architectural vision and system design for core AI/ML services
Lead complex, multi-quarter initiatives from inception to global deployment
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Chicago, United States; New York, US; San Francisco, United States
Full-time
Design and build large-scale deep learning infrastructure and platforms for distributed model training
Ensure low-latency and high-availability at enterprise scale
Partner with Product Management, Core Engineering, and executives to align ML capabilities with business strategy
Translate abstract product requirements into technical designs
Mentor and guide senior and mid-level data scientists and engineers
Establish standard methodologies and code quality expectations
Lead architecture design reviews
Work with AI training infrastructure components (accelerators, network fabrics, CUDA, NCCL, RDMA) and big data ecosystems (Databricks, Spark, Kubernetes, Kafka, Prometheus)
Design, develop, and support robust CI/CD pipelines for AI/ML services
Ensure smooth transition of models from research to production
Requirements
PhD/Master’s degree in computer science, mathematics, statistics, or equivalent experience
7+ years of machine learning experience in industry
Proven track record operating at Lead, Principal, or Staff level
Deep expertise in designing complex ML systems, ranking infrastructures, and data pipelines
Extensive production experience with ML frameworks such as PyTorch, JAX, or TensorFlow
Strong production-grade programming skills in Python, Go, Java, or C++
Deep understanding of software design principles and algorithms
Ability to work independently in ambiguous environments
Experience mentoring and collaborating with engineering talent
