Staff ML Engineer: Lead Scalable AI Systems

Aimlroles; 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

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.