Adobe Firefly Lead Engineer - Performance & Scalability
About Adobe
Changing the world through digital experiences is what Adobe’s all about. We empower everyone—from emerging artists to global brands—to design and deliver exceptional digital experiences. Our mission is to create an inclusive environment of innovation where everyone has access to equal opportunities.
About the Role
- Position: Lead Engineer, Performance & Scalability for Generative AI
- Scope: Optimize AI pipelines for flagship products such as Photoshop, Illustrator, Express, firefly.adobe.com
- Responsibilities include optimizing high-performance AI systems supporting millions of users, and working with ML researchers, infrastructure engineers, applied scientists.
Responsibilities
- Architect and optimize ML pipelines for scalable inference
- Develop high-throughput serving pipelines with low-latency execution
- Collaborate to enable model serving optimizations: tensor parallelism, quantization, distillation, caching
- Develop automated monitoring and profiling tools
- Optimize GPU resource management in cloud environments
- Conduct load testing for high-traffic scenarios
- Transition models from experimentation to production deployment
- Establish scalable, cloud-native ML architecture standards
Qualifications
- 8+ years in ML infrastructure and scalable AI systems
- MS or PhD in Computer Science or related field
- Strong programming skills in Python and C++
- Experience with cloud deployment: AWS, Kubernetes, Ray
- Knowledge of ONNX, TensorRT, AOT compilation
- Experience with cloud-native architectures, autoscaling, fault tolerance
- GPU orchestration skills: CUDA, accelerated inference
- Familiarity with profiling tools: Nsight, PyTorch Profiler, perf
- Ability to work in fast-paced, collaborative environments
Why Join Us?
Join Firefly, Adobe’s groundbreaking family of AI models, to shape the future of creativity and content creation.
Compensation & Legal Notices
- U.S. pay range: $162,000 -- $301,200 annually
- Role specifics regarding incentives and equity
- Equal opportunity employer with considerations for applicants' legal rights and accommodations.
Job Highlights
Qualifications
- 8+ years of experience in ML infrastructure
- Advanced degrees in computer science or related fields
- Proficiency in Python and C++
- Cloud deployment expertise
- Model optimization frameworks knowledge
- Cloud-native architecture experience
- GPU orchestration expertise
- Profiling tools experience
- Adaptive to fast-paced environments
Benefits
- Competitive salary range
- Incentives and long-term incentives options
Core Responsibilities
- Optimize and scale AI pipelines
- Collaborate across teams for deployment
- Design for scalability and high performance
- Automate system monitoring and resource management
- Lead efforts from experimental models to production
Tags
AI, Machine Learning, Cloud Computing, GPU, Scalability