Go Developer
GPUNET
Bengaluru, Karnataka, IndiaFresher4h agovia LinkedIn
About the Role
This is a flexible role for a Go Developer Intern at Gpu.net, focusing on AI Inference Infrastructure. The internship is for 3 months, with the possibility of a full-time offer. Interns will work on real production systems from week one.
Key Responsibilities
Depending on cluster needs and interests, responsibilities will include rotating across:
- API Gateway & Request Path:
- Build and improve the inference gateway in Go, focusing on routing, auth, API keys, rate limiting, and quotas.
- Handle streaming responses (SSE/WebSockets) for text and audio, and file/URL-based responses for images and video.
- Implement input validation, request queuing, and load balancing across nodes and models.
- Observability & Metrics:
- Build services to collect node, accelerator, and model-level metrics (throughput, latency, tokens/sec, utilization, errors).
- Instrument services with Prometheus/OpenTelemetry and build Grafana dashboards and alerts.
- Implement usage metering and per-customer token accounting for billing.
- Internal Tools & Cluster Operations:
- Develop CLI tools and internal services for deploying models, health checks, and node management.
- Automate provisioning, upgrades, and incident response.
- Contribute to tasks required to keep the cluster running reliably.
Requirements & Tech Stack
- Solid fundamentals in Go (goroutines, channels, context, error handling, testing), or strong skills in another language with a willingness to learn Go.
- Understanding of HTTP, REST APIs, and basic networking.
- Comfortable working on Linux and the command line.
- Familiarity with Git and writing clean, tested code.
- Curiosity about how AI models are served in production.
Nice to Have
- Experience with Docker / Kubernetes.
- Prometheus, Grafana, or any observability stack.
- gRPC, Redis, PostgreSQL, message queues.
- Exposure to LLM serving (vLLM, OpenAI-compatible APIs, tokenizers).
- Open-source contributions or personal projects in Go.
What You'll Get
- Hands-on work with a production AI cluster.
- Direct mentorship from engineers.
- Ownership of real features that ship to customers.