Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

About the Role

• Position: Lead Engineer (Performance and Scalability for Generative AI)
• Products: Photoshop, Illustrator, Express, firefly.adobe.com
• Responsibilities:
  • Optimize high-performance, scalable AI pipelines to support millions of users worldwide.
  • Collaborate with machine learning researchers, infrastructure engineers, and applied scientists.
  • Support deployment, scaling, and monitoring of generative AI models.
• Note: Does not involve directly training, quantization, or tensor parallelism.

Responsibilities

• Architect and optimize ML pipelines for scalable inference on cloud GPU infrastructure (e.g., AWS P5 instances).
• Develop and maintain high-throughput serving pipelines for generative AI models ensuring low-latency performance.
• Design systems supporting tensor parallelism, quantization, distillation, and caching.
• Develop automated monitoring/profiling tools for system efficiency.
• Optimize GPU resource allocation and orchestration.
• Implement scalable load testing frameworks.
• Transition models from experimentation to production-deployments.
• Establish methodologies for scalable, cloud-native ML architectures.

Qualifications

• 8+ years’ experience in ML infrastructure and scalable AI systems.
• MS or PhD in computer science or related field.
• Skilled in Python and C++.
• Experience with deploying large-scale ML models in cloud environments (AWS, Kubernetes, Ray).
• Familiarity with ONNX, TensorRT, AOT compilation.
• Knowledge of cloud-native architectures and autoscaling strategies.
• Proficiency in GPU orchestration, CUDA, inference techniques.
• Experience with profiling tools like Nsight, PyTorch Profiler, perf.
• Capable of working in a fast-paced, multi-disciplinary team environment.

Benefits

• U.S. salary range: $162,000 – $301,200 annually.
• Compensation varies based on location, experience, and skills.
• Sales roles may include commission; non-sales roles include base salary and annual incentives.
• Long-term incentives such as equity awards may be available.

Additional Information

• Fair Chance Ordinances: Consideration for applicants with arrest or conviction records.
• Colorado: Application window remains open until at least the specified date.
• Massachusetts: No lie detector tests required for employment.
• Equal Opportunity Employer: No discrimination based on protected characteristics.
• Accessibility: Accommodation requests via email or call.

Job Highlights

Qualifications

• 8+ years experience in ML infrastructure & scalable AI systems
• MS or PhD in computer science or related
• Programming skills in Python & C++, ML pipeline & deployment expertise
• Cloud deployment (AWS GPU, Kubernetes, Ray)
• Experience with ONNX, TensorRT, AOT
• Cloud-native architecture & autoscaling
• GPU orchestration, CUDA, inference techniques
• Profiling tools (Nsight, PyTorch Profiler, perf)
• Adaptability to fast-paced environments

Benefits

• Salary range: $162,000 - $301,200
• Compensation structures vary for sales and non-sales roles
• Benefits including equity, incentives, and long-term bonuses

Responsibilities

• Optimize and scale AI pipelines
• Collaborate across teams for deployment
• Support scalable inference on cloud infrastructure
• Develop monitoring & profiling tools
• Model transition from experiments to production
• Establish scalable ML architectures

This role offers a strategic opportunity to impact the future of generative AI at Adobe.

Job Highlights

Qualifications

• Over 8 years of experience in building high-performance ML infrastructure and scalable AI systems.
• Master's or PhD in Computer Science or related field.
• Strong coding skills in Python and C++.
• Experience in deploying large-scale ML models in cloud environments such as AWS, Kubernetes, Ray.
• Familiar with model optimization frameworks like ONNX and TensorRT.
• Knowledge of cloud-native and autoscaling architectures.
• Proficiency in GPU orchestration and CUDA.
• Hands-on experience with profiling tools such as Nsight, PyTorch Profiler, and perf.
• Ability to excel in a fast-paced, collaborative environment.

Benefits

• Salary range in the US: $162,000 – $301,200 annually.
• Compensation varies based on location, skills, and experience.
• For non-sales roles, includes base salary and incentives.
• Potential eligibility for long-term incentives like equity awards.

Responsibilities

• Lead the optimization of AI pipelines supporting millions of users.
• Collaborate with researchers and engineers for deployment and scaling.
• Support scalable inference on cloud GPU resources.
• Develop monitoring, profiling, and load testing tools.
• Transition models from R&D to production.
• Define methodologies for scalable, cloud-based ML architectures.

This is a key strategic role to shape the future of generative AI at Adobe.