招聘
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Learning Budget
•Healthcare
•401k
•Equity
•Learning
Required Skills
Machine learning
LLM
GPU
Distributed training
Model fine-tuning
DevOps
Kubernetes
Docker
Python
A/B testing
API design
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!
Key Responsibilities
· Platform Development and Evangelism:
- Build scalable AI platforms that are customer-facing.
- Evangelize the platform with customers and internal stakeholders.
- Ensure platform scalability, reliability, and performance to meet business needs.
· Machine Learning Pipeline Design:
- Design ML pipelines for experiment management, model management, feature management, and model retraining.
- Implement A/B testing of models.
- Design APIs for model inferencing at scale.
- Proven expertise with MLflow, Sage Maker, Vertex AI, and Azure AI.
LLM Serving and GPU Architecture:
- Serve as an SME in LLM serving paradigms.
- Possess deep knowledge of GPU architectures.
- Expertise in distributed training and serving of large language models.
- Proficient in model and data parallel training using frameworks like Deep Speed and service frameworks like vLLM.
Model Fine-Tuning and Optimization:
- Demonstrate proven expertise in model fine-tuning and optimization techniques.
- Achieve better latencies and accuracies in model results.
- Reduce training and resource requirements for fine-tuning LLM and LVM models.
LLM Models and Use Cases:
- Have extensive knowledge of different LLM models.
- Provide insights on the applicability of each model based on use cases.
- Proven experience in delivering end-to-end solutions from engineering to production for specific customer use cases.
Dev
Ops and LLMOps Proficiency:
Proven expertise in DevOps and LLMOps practices. Knowledgeable in Kubernetes, Docker, and container orchestration. Deep understanding of LLM orchestration frameworks like Flowise, Langflow, and Langgraph.
Communication & Articulation
- Ability to explain complex AI/ML topics and design choices to technical and business audiences.
- Experience in presenting AI strategies and results to senior executives, highlighting impact.
- Ability to lead cross-functional discussions to clarify issues and achieve engineering consensus.
- Ability to persuade stakeholders and secures support on solution approaches.
Continuous Innovation & Adaptive Learning
- Proactively tracks emerging AI research, frameworks, and industry design patterns.
- Validates new concepts through quick experimentation and iterative fail-fast testing.
- Translates cutting-edge developments into practical improvements for production systems.
- Demonstrates a self-driven commitment to learning and adopting evolving AI technologies.
Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.
Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodationsadobe.com or call (408) 536-3015.
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About Adobe

Adobe
PublicA software company that provides its users with digital marketing and media solutions.
10,001+
Employees
San Jose
Headquarters
$126B
Valuation
Reviews
3.3
9 reviews
Work Life Balance
3.5
Compensation
3.8
Culture
3.2
Career
3.4
Management
2.8
58%
Recommend to a Friend
Pros
Good people and culture
Strong leadership and management support
Good employee benefits and perks
Cons
Inconsistent management quality
Poor treatment of contractors
Toxic leadership at director level
Salary Ranges
4,150 data points
Junior/L3
L2
L3
L4
L5
L6
Mid/L4
Senior/L5
Staff/L6
Junior/L3 · Data Scientist L2
0 reports
$175,386
total / year
Base
-
Stock
-
Bonus
-
$149,078
$201,695
Interview Experience
3 interviews
Difficulty
3.0
/ 5
Interview Process
1
Online Assessment
2
Technical Interview
3
Team Matching
Common Questions
Technical/Coding Questions
Online Assessment
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