Sr Machine Learning Services Engineer

The Opportunity    

Adobe is looking for a Senior Machine Learning Services Engineer to help bring new AI and Generative AI capabilities into production across Adobe’s flagship creative products. In this role, you will work at the intersection of applied ML, large-scale cloud services, and GPU-optimized inference, partnering closely with Adobe Research and product engineering teams to translate cutting-edge models into reliable, high-performance production services. 

You will join a team responsible for the ML cloud services that power features used daily by millions of creators across products like Photoshop, Lightroom, Illustrator, Express, Stock, and enterprise surfaces. This is a hands-on senior IC role with meaningful technical ownership and direct impact on customer-facing AI experiences. 

 What you’ll do   

• Design, build, and operate backend cloud services that power ML and Generative AI features across multiple Adobe products 

• Build an agentic end to end pipeline for tech transfer modernization 

• Architect and optimize GPU-accelerated ML inference pipelines for scalability, cost efficiency, and reliability in production 

• Optimize ML models for production inference, including techniques such as quantization, pruning, graph optimization, batching, and hardware-aware tuning to improve latency, throughput, and cost 

• Analyze and improve performance, quality, stability, and throughput of end-to-end AI workflows 

• Lead the integration of new ML models into production systems, including model validation, regression testing, and quality evaluation 

• Build and maintain CI/CD pipelines supporting a suite of ML-backed microservices 

• Collaborate closely with Research, Product, and Engineering partners to productionize new ML capabilities 

• Ensure services meet production standards for observability, monitoring, logging, and incident response 

• Participate in on-call and production support, contributing to a culture of operational excellence   

What you need to succeed   

• 5+ years of experience building, optimizing, and operating ML systems in production, including GPU-based workloads 

• Proven experience designing large-scale, reliable cloud services with strong performance and availability requirements 

• Strong background in model serving and inference optimization, including techniques for conversion, compression, and orchestration 

• Hands-on experience with computer vision and/or generative models, such as GANs, diffusion models, CLIP, or MLLMs 

• Expertise