hackajob is collaborating with Oracle to connect them with exceptional professionals for this role.
Description
We're hiring a Platform Software Engineer to help build the execution layer behind OCI's AI and GPU growth motion. You'll work across Oracle data platforms, GPU scheduling, orchestration pipelines, and MLOps agentic tooling — turning customer demand into production-grade systems that scale across our cluster fleet. This is a builder role on a small, high-leverage team.
What you'll do
- Integrate with Oracle data platforms (OCI Streaming, 23ai, Object Storage, Data Flow) to move training and inference data reliably across customer and internal pipelines.
- Build and extend GPU schedulers and capacity-aware placement logic for A100, H100, H200, and Blackwell fleets.
- Develop orchestration pipelines for training, fine-tuning, and inference workloads using Kubernetes, Argo, and Slurm where appropriate.
- Ship MLOps agentic tooling — observability, automated triage, cost and SLO agents — that reduces operator load on large GPU deployments.
- Partner with PMs, SAs, and customer-facing teams to convert field requirements into reusable components, not one-off scripts
#LI-ES2
Responsibilities
What we're looking for:
- 3-6 years of software engineering experience, ideally in distributed systems, data platforms, or ML infrastructure.
- Strong Python; working knowledge of Go or Rust is a plus.
- Hands-on experience with Kubernetes, container runtimes, and at least one workflow engine (Argo, Airflow, Prefect, Temporal).
- Familiarity with GPU workloads, CUDA toolchains, or inference serving frameworks (vLLM, TensorRT-LLM, Triton).
- Experience with LLM agent frameworks (LangGraph, CrewAI, or similar) is a strong plus.
- Comfort working in ambiguity, shipping iteratively, and reasoning about topology — not just features.
Nice to have:
- Prior work on multi-cloud or hybrid deployments.
- Exposure to QEC, quantum-classical hybrid workloads, or scientific computing.
- Open-source contributions to the AI infra ecosystem.
Qualifications
Disclaimer:
Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements.
Range and benefit information provided in this posting are specific to the stated locations only
US: Hiring Range in USD from: $79,200 to $209,500 per annum. May be eligible for bonus and equity.
Oracle maintains broad salary ranges for its roles in order to
Description
We're hiring a Platform Software Engineer to help build the execution layer behind OCI's AI and GPU growth motion. You'll work across Oracle data platforms, GPU scheduling, orchestration pipelines, and MLOps agentic tooling — turning customer demand into production-grade systems that scale across our cluster fleet. This is a builder role on a small, high-leverage team.
What you'll do
- Integrate with Oracle data platforms (OCI Streaming, 23ai, Object Storage, Data Flow) to move training and inference data reliably across customer and internal pipelines.
- Build and extend GPU schedulers and capacity-aware placement logic for A100, H100, H200, and Blackwell fleets.
- Develop orchestration pipelines for training, fine-tuning, and inference workloads using Kubernetes, Argo, and Slurm where appropriate.
- Ship MLOps agentic tooling — observability, automated triage, cost and SLO agents — that reduces operator load on large GPU deployments.
- Partner with PMs, SAs, and customer-facing teams to convert field requirements into reusable components, not one-off scripts
#LI-ES2
Responsibilities
What we're looking for:
- 3-6 years of software engineering experience, ideally in distributed systems, data platforms, or ML infrastructure.
- Strong Python; working knowledge of Go or Rust is a plus.
- Hands-on experience with Kubernetes, container runtimes, and at least one workflow engine (Argo, Airflow, Prefect, Temporal).
- Familiarity with GPU workloads, CUDA toolchains, or inference serving frameworks (vLLM, TensorRT-LLM, Triton).
- Experience with LLM agent frameworks (LangGraph, CrewAI, or similar) is a strong plus.
- Comfort working in ambiguity, shipping iteratively, and reasoning about topology — not just features.
Nice to have:
- Prior work on multi-cloud or hybrid deployments.
- Exposure to QEC, quantum-classical hybrid workloads, or scientific computing.
- Open-source contributions to the AI infra ecosystem.
Qualifications
Disclaimer:
Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements.
Range and benefit information provided in this posting are specific to the stated locations only
US: Hiring Range in USD from: $79,200 to $209,500 per annum. May be eligible for bonus and equity.
Oracle maintains broad salary ranges for its roles in order to
Senior Core Infrastructure Engineer in remote at Unknown Company
This position is listed as full time and hybrid.