refresh

Trending Companies

Trending

Jobs

JobsAMD

Senior Software Engineer – AI Infrastructure & Orchestration

AMD

Senior Software Engineer – AI Infrastructure & Orchestration

AMD

Helsinki

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Flexible PTO policy

Wellness benefits

Top Tier compensation with equity

Health, dental, and vision coverage

Parental leave program

Remote work flexibility

Required Skills

Python

TensorFlow

PyTorch

Back

Senior Software Engineer – AI Infrastructure & Orchestration

JOB_DESCRIPTION.SHARE.HTML
CAROUSEL_PARAGRAPH

  • JOB_DESCRIPTION.SHARE.HTML
  • Helsinki, Finland
  • Engineering
  • 68251

mail_outline
Get future jobs matching this search
Loginor Register

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:

We are looking for a motivated and skilled Software Engineer to help us build advanced GPU orchestration capabilities that power modern AI and machine learning workloads in Kubernetes environments.

In this role, you’ll contribute to the development of systems that optimize GPU utilization, enable fair and efficient scheduling, and support a wide spectrum of AI jobs—from distributed training to real-time inference.

You will be part of a core team developing open-source tooling that bridges the gap between infrastructure and AI frameworks, ensuring that cutting-edge models can be deployed, scheduled, and scaled reliably on cloud-native GPU infrastructure.

Please note: The candidate must be based in Finland or Sweden and will be expected to come to the office from time to time, though the setup is highly flexible.

KEY RESPONSIBILITIES:

  • Design and implement Kubernetes-native systems to orchestrate GPU workloads efficiently.

  • Develop features in Golang, including custom Kubernetes controllers and CRDs.

  • Contribute to job scheduling mechanisms such as gang scheduling, fair sharing, and opportunistic compute allocation.

  • Integrate with existing AI/ML frameworks and distributed systems (e.g., Ray, Py Torch, Tensor Flow).

  • Build tools and interfaces (e.g., CLI) to make complex GPU orchestration intuitive for data scientists and ML engineers.

  • Collaborate on architecture, performance optimizations, and observability for large-scale AI workloads.

  • Contribute to and maintain open-source software, participate in community discussions, and write documentation.

KEY REQUIREMENTS:

  • Strong experience with Golang and Kubernetes internals (e.g., operators, controllers, scheduling, CRDs).

  • Familiarity with Python and ML/AI tooling (e.g., training pipelines, model inference, Ray, or similar).

  • Solid understanding of container orchestration, cloud-native infrastructure, and GPU workloads in production.

  • Ability to work autonomously in a fast-paced environment and communicate effectively in a remote team.

NICE TO HAVE:

  • Experience building distributed systems and working with open-source projects.

  • Experience contributing to or maintaining Kubernetes-native ML tooling (e.g., Kubeflow, Ray, Kueue).

  • Background in ML research, distributed training, or infrastructure for LLMs and deep learning.

  • Contributions to open-source communities in cloud-native or ML ecosystems.

Location:

  • Helsinki, Finland or Stockholm, Sweden

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.
Apply JOB_DESCRIPTION.SHARE.HTML
CAROUSEL_PARAGRAPH
JOB_DESCRIPTION.SHARE.HTML

Total Views

0

Apply Clicks

0

Mock Applicants

0

Scraps

0

About AMD

AMD

AMD

Public

A 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 · Data Analyst L2

0 reports

$76,430

total / year

Base

$30,572

Stock

$38,215

Bonus

$7,643

$53,501

$99,359

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