Senior Machine Learning Engineer
Adobe
full-time
Posted on:
Location Type: Hybrid
Location: San Francisco • California • 🇺🇸 United States
Visit company websiteSalary
💰 $172,500 - $306,625 per year
Job Level
Senior
Tech Stack
CloudDistributed SystemsGoJavaKafkaMicroservicesPythonSpark
About the role
- Lead development and contribute to building the complete AI stack for Adobe Express — covering Agentic AI, Construct AI, Imaging AI, Motion AI, and Personalization AI.
- Develop and operationalize end-to-end systems — integrating microservices, data pipelines, LLM orchestration layers, in-house and third-party models, databases, caches, session analytics, and evaluation systems into a cohesive architecture.
- Develop large-scale data and inference infrastructure to support model training, fine-tuning, evaluation, and deployment — employing Spark, Kafka, Flink, and other distributed frameworks.
- Develop high-performance runtime services for inference and orchestration with strong observability, fault tolerance, and latency guarantees.
- Apply strong caching and storage tactics to enhance efficiency and cost-effectiveness for various AI workloads.
- Lead development of experimentation and evaluation systems, encompassing session-level analytics, feedback loops, and quality metrics that drive continuous improvement.
- Work closely with applied research, product, and platform teams to implement LLMs and other AI models into customer-facing services.
- Mentor junior engineers and scale the team to drive collectively the charter of Agentic AI for Adobe Express.
Requirements
- 8+ years of experience in large-scale distributed systems AI infrastructure, or ML platform engineering.
- Proven expertise in building and scaling data pipelines, real-time streaming systems, and event-driven architectures (Kafka, Spark, Flink, etc.).
- Strong background in API development, caching strategies, database development, and performance optimization for large-scale serving systems.
- Hands-on experience with LLM orchestration frameworks, model routing, and multi-model inference.
- Proficiency in Python, Java, C++, or Go, with an emphasis on distributed systems, cloud-native deployment, and performance tuning.
- Familiarity with Agentic AI patterns — reasoning loops, memory persistence, task decomposition, and multi-agent coordination.
- Strong communication and collaboration skills, with experience influencing cross-functional technical direction.
Benefits
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
large-scale distributed systemsAI infrastructureML platform engineeringdata pipelinesreal-time streaming systemsevent-driven architecturesAPI developmentcaching strategiesdatabase developmentperformance optimization
Soft skills
strong communicationcollaboration skillsmentoringinfluencing technical direction