DataOps Engineer (AI Platform Engineer) at Exness jobs for internal candidates

✨ The Stack take on this Exness jobs for internal candidates job

• 🏢 Exness jobs for internal candidates has 13 jobs here, 13 with visa sponsorship see all
• 🛂 Visa: Foreign Interest Company work permit. Minimum salary: €2,500 a month guide
• 💡 No salary shown. Ask Exness jobs for internal candidates if it is above the minimum.

Updated 2026-11-05, from our data and official sources.

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About the role

Responsibilities:
- Design, deploy and operate an on-prem AI platform for multi-node GPU clusters and Kubernetes.
- Collaborate on GPU server selection, high-performance networking and RDMA-enabled cluster configuration.
- Manage GPU partitioning/MIG, scheduling and runtime integration to maximise utilization and reliability.
- Deploy and maintain model serving runtimes (vLLM, ONNX, SGLang, Nvidia Triton, KServe) and benchmarking setups.
- Build CI/CD pipelines and tooling for model packaging, versioning, deployment and reproducible delivery.
- Implement model lifecycle tooling: experiment tracking, registries and support for fine-tuning (e.g., LoRA).
- Create observability and tracing for GPU workloads and inference flows (utilisation, memory, throughput, latency).
- Run performance tests and benchmarks across runtimes and hardware; identify and resolve bottlenecks.
- Ensure platform security and compliance for model serving and data handling.

Requirements:
- Bachelor’s or Master’s in CS, Engineering or related field and 5+ years in infrastructure/platform or distributed systems.
- Strong Kubernetes experience running production workloads and Linux proficiency.
- Programming skills in Python and/or Go; experience building automation and CI/CD for ML workloads.
- Hands-on experience with GPU infrastructure (NVIDIA/AMD), multi-GPU clusters and MIG configurations.
- Familiarity with model serving runtimes (Triton, KServe, vLLM, ONNX) and model lifecycle tools (MLflow).
- Understanding of high-performance networking, RDMA, GPU scheduling and performance benchmarking.
- Good troubleshooting, observability and system optimisation skills.

Responsibilities

Design and operate an on-prem AI platform for deploying and scaling models across multi-node GPU clusters and Kubernetes. Build reliable infrastructure for large-scale model inference, including CI/CD pipelines and observability tools for GPU workloads.

Requirements

Requires a degree in Computer Science or Engineering with 5+ years of experience in platform engineering or distributed systems. Proficiency in Kubernetes, Python/Go, and experience with GPU infrastructure and model serving runtimes is essential.

Key skills

• Kubernetes — in 585 other listings on The Stack
• GPU Infrastructure — in 6 other listings on The Stack
• Python — in 1200 other listings on The Stack
• Go — in 230 other listings on The Stack
• Distributed Systems — in 342 other listings on The Stack
• Model Serving — in 9 other listings on The Stack
• CI/CD — in 630 other listings on The Stack
• Observability — in 305 other listings on The Stack
• Linux
• vLLM
• Nvidia Triton
• KServe
• MLflow
• RDMA
• Performance Testing
• GPU Scheduling

On The Stack (as of 2026-11-05)

• Exness jobs for internal candidates has 12 other listings on The Stack, 12 of them marked as offering visa sponsorship.
• 34 visa-sponsored jobs in Cyprus on The Stack, posted in the last 60 days.
• 56 visa-sponsored platform engineer jobs in Europe on The Stack, posted in the last 60 days.

Frequently asked questions about Exness jobs for internal candidates

Is this DataOps Engineer (AI Platform Engineer) role still open?

It was posted on 2026-05-15. Listings more than 30 days old may no longer be active, so check Exness jobs for internal candidates's site before applying.

Does Exness jobs for internal candidates offer visa sponsorship?

This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Exness jobs for internal candidates's site.

Where is this role located?

The listing gives the location as Cyprus. It is marked on-site.

What skills does this role ask for?

The listing names: Kubernetes, GPU Infrastructure, Python, Go, Distributed Systems, Model Serving, CI/CD, Observability, Linux, vLLM, Nvidia Triton, KServe, MLflow, RDMA, Performance Testing, GPU Scheduling.