Software Engineer, Inference

🔥 1 minute ago

🇪🇺 Europe – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Luma AI

WebsiteLinkedInAll Job Openings

2 - 10 employees

🤖 Artificial Intelligence

☁️ SaaS

📱 Media

💰 $90M Series B on 2025-01

Artificial Intelligence • SaaS • Media

Luma AI is a Palo Alto–based company building multimodal generative AI models and creative workflow tools focused on video, image, audio, and text production. Luma offers models and products such as Ray (video generation), UNI-1/Uni-1. 1 (brand intelligence models), and an API/enterprise offerings that allow creative teams to generate, edit, and direct cinematic-quality assets with brand continuity. They emphasize frontier research (Open Physical AI Lab), in-house model development, and products for creative teams, agencies, and production services. Luma also provides APIs, enterprise plans, a creative partner program, and learning resources.

📋 Description

• Own how Luma's models get served through inference-engine integration, deployment scaling, and GPU fleet utilization • Integrate new model architectures into the inference engine • Collaborate across research, engineering, and infrastructure to optimize model efficiency and deployments • Build internal tooling to measure, profile, and track inference jobs and workflows • Automate, test, and maintain inference services for uptime and reliability • Manage and optimize inference workloads across clusters and hardware providers • Scale deployments across thousands of machines • Build scheduling systems that optimize GPU resources while meeting SLOs • Maintain CI/CD for model checkpoints and SDKs • Learn the inference stack and diagnose reliability or utilization issues during the first 30 days • Integrate a model or ship tooling/scheduling improvements during days 30–60 • Harden deployment pipelines and scheduling across clusters and providers during days 60–90

🎯 Requirements

• Strong Python and system-architecture skills • Experience deploying models with PyTorch, Hugging Face, vLLM, SGLang, TensorRT-LLM, or similar • Experience with queues, scheduling, traffic control, and fleet management at scale • Experience with Linux, Docker, and Kubernetes • Experience with orchestration, deployment, and scheduling • Familiarity with Redis and S3-compatible storage • Nice to have: modern networking stacks including RDMA (RoCE, InfiniBand, NVLink) • Nice to have: high-performance large-scale ML systems (100+ GPUs) • Nice to have: CUDA, and FFmpeg or multimedia processing

🏖️ Benefits

• Equal opportunity employer • Voluntary diversity and inclusion survey participation; refusal does not affect the job application • Remote work arrangement