Software Engineer – Ads AI Infrastructure (New Grad / PhD Welcome)

Mintegral; Seattle (WA); On-site; USD 140,000 - 210,000; Full time

Job summary

Mintegral is seeking exceptional Software Engineers who are passionate about AI infrastructure, high-performance computing, and building reliable systems at massive scale. This role targets new graduates and early-career engineers at the intersection of distributed systems and ML infrastructure.

Join a team building AI-powered ad decision systems, serving billions of requests with GPU-accelerated training and inference pipelines.

Qualifications

• Bachelor's, Master's, or Ph.D. in Computer Science, Software Engineering, AI, Data Science, or related fields.
• Strong programming skills in C++, Python, Java, Go, or similar languages.
• Strong foundation in algorithms, data structures, operating systems, distributed systems, and computer architecture.
• Strong interest in machine learning systems, AI infrastructure, and high‑performance computing.

Responsibilities

• Design and build high-performance AI infrastructure supporting large-scale advertising machine learning systems.
• Develop GPU-accelerated machine learning training and inference infrastructure, including distributed training and model optimization.
• Build and optimize ML systems using PyTorch, TorchRec, and distributed training frameworks.
• Design and implement high-throughput, low-latency real-time decision systems serving massive volumes of advertising requests.
• Build data and feature pipelines for embeddings, multimodal features, and real-time feature serving.
• Develop scalable model serving infrastructure for production ML applications.
• Improve system performance through parallel computing, GPU acceleration, and memory optimization.
• Collaborate with ML engineers and researchers to productionize state-of-the-art models.

Skills

C++

Python

Java

Go

Distributed systems

GPU programming

Machine learning systems

English communication

Education

Bachelor's degree in Computer Science

Master's degree in related field

Ph.D. in relevant field

Tools

PyTorch

TorchRec

DeepSpeed

CUDA

Distributed training frameworks

Job description

Mintegral is a leading programmatic and interactive mobile advertising platform. Focused on the APAC region and radiating out globally. Powered by advanced AI technology, we provide global advertisers and developers with innovative, comprehensive experiences. With our efficient mobile marketing and monetization solutions, we help our clients exceed their marketing goals.

As Mobvista’s self-developed programmatic platform, since launched in 2015, Mintegral has quickly grown to become one of the largest mobile advertising platforms in Asia. We offer a full stack of programmatic products and services, including our Self-service Platform, DSP, SSP, Ad Exchange and DMP. We have also created the Mindworks Creative Studio, which offers publishers and brands cutting-edge creative solutions, from traditional creative right through to the latest interactive ad formats. For more information, please visit our website https://www.mintegral.com/en

About the Team

We are building next-generation advertising intelligence platforms that power large-scale, real-time decision systems. Our team develops AI infrastructure and machine learning systems that enable advanced advertising solutions, including large-scale model training, high-performance inference, feature platforms, and embedding services.

We are looking for exceptional Software Engineers who are passionate about AI infrastructure, high-performance computing, and building reliable systems at massive scale. This role is ideal for new graduates and early-career engineers who want to work at the intersection of distributed systems, GPU computing, and machine learning systems.

Responsibilities

• Design and build high-performance AI infrastructure supporting large-scale advertising machine learning systems.
• Develop GPU-accelerated machine learning training and inference infrastructure, including distributed training, mixed precision training, and large-scale model optimization.
• Build and optimize ML systems using modern frameworks and technologies such as PyTorch, TorchRec, and distributed training frameworks.
• Design and implement high-throughput, low-latency real-time decision systems serving massive volumes of advertising requests.
• Build efficient data and feature pipelines supporting large-scale embeddings, multimodal features, and real-time feature serving.
• Develop scalable model serving infrastructure for production machine learning applications.
• Optimize system performance through parallel computing, GPU acceleration, memory optimization, and advanced system design.
• Collaborate closely with machine learning engineers and researchers to productionize state-of-the‑art models.
• Build reliable, scalable, and maintainable infrastructure for next‑generation advertising AI systems.

Basic Qualifications

• Bachelor's, Master's, or Ph.D. degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, Operations Research, or related fields.
• Strong programming skills in C++, Python, Java, Go, or similar languages.
• Strong foundation in algorithms, data structures, operating systems, distributed systems, and computer architecture.
• Strong interest in machine learning systems, AI infrastructure, and high‑performance computing.
• Ability to solve complex engineering problems and quickly learn new technologies

Preferred Qualifications

• Experience with GPU programming (CUDA), high-performance computing, or system‑level performance optimization.
• Experience with machine learning systems (ML Systems), large‑scale AI infrastructure, or distributed training platforms.
• Familiarity with PyTorch distributed training, TorchRec, DeepSpeed, FSDP, model parallelism, data parallelism, or 2D parallel training strategies.
• Experience building large-scale machine learning infrastructure, including training platforms, model serving systems, feature platforms, or embedding serving systems.
• Experience with real‑time inference systems, low‑latency services, or large‑scale data processing.
• Research projects, internships, or open‑source contributions related to AI infrastructure are highly valued.
• Strong research ability and problem‑solving skills.
• Passion for online advertising, recommendation systems, and intelligent decision-making

Why Join Us

• Work on challenging AI and machine learning problems at the intersection of advertising, recommendation, and large‑scale decision systems.
• Build technologies that impact hundreds of millions of advertising requests through real-time intelligent decision‑making.
• Directly contribute to improving advertiser performance and ROI through advanced AI systems.
• Collaborate with talented engineers and researchers working on cutting‑edge ML infrastructure and algorithms.
• Opportunity to work with large‑scale models, GPU computing, distributed training, and production AI systems.