Software Engineer – AI Infrastructure & Orchestration

WHAT YOU DO AT AMD CHANGES EVERYTHING

We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences - the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives.

AMD together we advance_

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, PyTorch, TensorFlow).
• 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.

Finland or 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.

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