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Software Golang Engineer (Kubernetes)
Contract type
Ongoing
Work mode
Remote
Experience
3 years
Job description
An experienced Golang Engineer role at Gcore to build Kubernetes-native AI infrastructure and tooling for scalable inference and training workloads. The engineer designs and implements AI inference and model training cloud products optimized for Kubernetes.
At a glance
- Work mode
- Remote
What you'll do
- Design and implement AI inference and model training cloud products optimized for Kubernetes - from autoscaling inference servers to distributed training jobs across GPU fleets
- Write clean, efficient, and maintainable Go code to power Kubernetes controllers, operators, and custom resources supporting AI workloads
- Build APIs, CLIs, and developer tools that simplify the deployment, lifecycle management, and monitoring of AI applications
- Develop features that optimize serverless container workflows for AI, ensuring fast cold starts, resource-efficient scaling, and workload isolation
- Contribute to system performance, reliability, and security, with a focus on AI-specific challenges such as GPU scheduling, job orchestration, and data throughput
- Stay on top of Kubernetes ecosystem advancements (e.g., K8s-native ML tooling, scheduling improvements, SIGs) and influence our product roadmap accordingly
What we're looking for
- Strong proficiency in Go programming, with experience in Kubernetes development, including controllers and operators
- Deep understanding of Kubernetes architecture, resource management, and container orchestration
- Experience working with Kubernetes APIs and custom resources (CRDs)
- Solid knowledge of cloud-native technologies and frameworks, including Docker and Helm
- Strong problem-solving skills, with a passion for tackling complex challenges in distributed systems
- Excellent communication skills and the ability to thrive in a collaborative, team-oriented environment
Nice to have
- Experience with Python programming language
- Experience with developing AI/ML pipelines or integrating AI frameworks (e.g., TensorFlow, PyTorch) into Kubernetes
- Understanding of GPU scheduling and optimization in Kubernetes environments
- Knowledge of security best practices in Kubernetes, including role-based access control (RBAC) and container security
- Contributions to open-source Kubernetes projects or cloud-native communities
Benefits
- Competitive compensation
- Flexible working hours and hybrid or remote options, depending on your role
- Work from anywhere in the world for up to 45 days per year
- Private medical insurance for you and your family*
- Extra paid vacation and sick leave days*
- Support for life's important moments and celebrations
- Language courses to help you connect and grow
- Modern, welcoming offices with snacks, drinks, and entertainment*
- Team sports and social activities*
Apply
Direct apply at Gcore
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About Gcore
Connect the world to AI, anywhere, anytime
A global provider of infrastructure and software solutions for AI, cloud, network, and security, powering everything from real-time communication and streaming to enterprise AI and secure web applications. With 210+ edge locations, 50+ cloud regions, and thousands of GPUs.
Mission
To connect the world to AI, anywhere, anytime.
Key facts
- 550+ professionals
- Infrastructure and software solutions for AI, cloud, network, and security
- 210+ edge locations
- 50+ cloud regions
- Thousands of GPUs
- Global team of 550+ professionals
Partners & customers
IntelNVIDIADellEquinix