Senior ML Engineer, Real-Time AdTech Platforms

Digital Turbine Media, Inc.; New York (NY); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Digital Turbine is seeking a Senior Machine Learning Engineer to design and scale ML systems powering ad ranking, bidding, and next-best-action recommendations. You will deploy production pipelines handling billions of events with low latency and partner across data science, data engineering, and product teams to drive CTR, CVR, and ROAS improvements.

You should have 8+ years in production ML, strong Python, and experience with PyTorch/TensorFlow, Spark, and real-time systems.

Qualifications

• 8+ years building and deploying ML systems in production at scale, ideally in AdTech or real-time bidding.
• Strong software-engineering fundamentals and proficiency in Python (plus JS/Java/Scala/C++ a plus).
• Hands-on experience with modern ML frameworks and distributed data/compute systems.

Responsibilities

• Design, build, and deploy large-scale ML systems for ad ranking, click-through and conversion prediction, bid optimization, and next-best-action recommendation.
• Build and operate production ML pipelines—feature engineering, distributed training, deployment, retraining, and monitoring.
• Leverage data assets across the product portfolio to enable real-time decisioning using broad feature sets.
• Optimize training and inference for compute efficiency, latency, and cost across distributed systems.
• Partner with Data Science, Data Engineering, and product teams to ship models that move business metrics and run online experiments.
• Stay current with applied ML research and bring innovative techniques to advertising and audience modeling.

Skills

ML systems

Python

Software engineering

AdTech experience

Distributed training

Education

MS/PhD in CS/ML

Tools

PyTorch

TensorFlow

JAX

Spark/Dataflow

Job description

Digital Turbine is seeking a Senior Machine Learning Engineer to design and scale ML systems powering ad ranking, bidding, and next-best-action recommendations. You will deploy production pipelines handling billions of events with low latency and partner across data science, data engineering, and product teams to drive CTR, CVR, and ROAS improvements.

You should have 8+ years in production ML, strong Python, and experience with PyTorch/TensorFlow, Spark, and real-time systems.