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Benefits & Perks
•Competitive salary and equity package
•Team events and activities
•Flexible work arrangements
•Parental leave
•Comprehensive health, dental, and vision insurance
•Generous paid time off and holidays
•Equity
•Flexible Hours
•Parental Leave
•Healthcare
Required Skills
TypeScript
Python
PostgreSQL
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DevOps Engineer
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- Warsaw, Poland
- Engineering
- 72192
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Job Description
WHAT YOU DO AT AMD CHANGES EVERYTHING:
At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.
THE ROLE:
AMD is seeking an accomplished DevOps software engineer to power our distributed ML and rendering infrastructure. As a remote team member (Poland), you will play a crucial role in enabling global collaboration for the next generation of AI and rendering workloads, delivering secure, automated, and resilient DevOps solutions that keep our North American data center and European teams in perfect sync.
THE PERSON:
The right candidate combines an automation mindset, deep expertise in on-premises infrastructure, on both customer and high-end server grade hardware. They thrive in distributed teams, communicate with clarity, and have a relentless drive for operational excellence and reliability. Comfortable supporting both high-performance render farms, machine learning infrastructure and NAS-driven data pipelines.
KEY RESPONSIBILITIES:
- Design, implement, and maintain CI/CD pipelines for ML and rendering workflows, enabling seamless model and data deployment.
- Automate and monitor the provisioning, scaling, and maintenance of ML servers and render workstations.
- Set up secure, high-bandwidth data workflows between North American data center and European endpoints using enterprise NAS.
- Streamline data pipelines between multiple data teams and modeling teams
- Troubleshoot and resolve infrastructure incidents, drive root-cause analysis, and implement preventive solutions.
- Collaborate daily with cross-functional teams in Europe and North America to support remote development/testing and modeling needs.
- Integrate security best practices throughout the deployment stack, including secrets management and compliance monitoring.
- Lead the development of infrastructure documentation, runbooks, and user guides to streamline onboarding and operational support.
- Stay up to date with new DevOps tools, infrastructure improvements, and performance optimization techniques.
PREFERRED EXPERIENCE:
- Strong background in Linux and Windows systems engineering, scripting (Python, Bash), and automation.
- Experience with enterprise render farms, large-scale NAS, and machine learning pipelines.
- Experience with on-premises infrastructure, complex system and integration with new and existing tooling
- Proficiency with infrastructure management and orchestration tools (Ansible, Packer or similar).
- Solid understanding of networking concepts, DHCP, DNS, TCP/IP stack
- Track record with CI/CD pipelines using GitHub Actions
- Experience with Kubernetes and Docker - with focus on machine learning frameworks (flyte, Kubeflow or similar)
- Experience working in a remote, globally distributed engineering environment.
- Habit of creating notes, documentation, requirements and presenting it to the team or stakeholders
- Good communication skills - be able to talk with stakeholders, investigate and 'make things done'
- Ability to work independently, figure out missing pieces to get to the final goal
- Nice to have prior experience with validation frameworks, especially graphic related
ACADEMIC CREDENTIALS:
- Engineering in Computer Science, Computer Engineering, or equivalent.
Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
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About AMD

AMD
PublicA semiconductor company that designs and develops graphics units, processors, and media solutions
10,001+
Employees
Santa Clara
Headquarters
Reviews
3.5
25 reviews
Work Life Balance
3.2
Compensation
4.1
Culture
3.6
Career
3.4
Management
3.1
65%
Recommend to a Friend
Pros
Good compensation and benefits
Positive work environment
Great management and coworkers
Cons
Poor work life balance
Micromanagement and excessive tracking
Too much pressure and workload
Salary Ranges
6 data points
L2
L3
L4
L5
L6
L2 · Cybersecurity Analyst L2
0 reports
$130,000
total / year
Base
$52,000
Stock
$65,000
Bonus
$13,000
$91,000
$169,000
Interview Experience
5 interviews
Difficulty
3.6
/ 5
Duration
14-28 weeks
Offer Rate
60%
Experience
Positive 20%
Neutral 20%
Negative 60%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Technical Interview
5
Hiring Manager Interview
6
Offer
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
Past Experience
System Design
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