The Role
The Data Reliability Engineer will enhance the resilience and scalability of data infrastructure, focusing on automation and reliability. Responsibilities include managing data pipelines, operating Kubernetes clusters, and defining observability standards.
Summary Generated by Built In
Where You Come In
As our models scale to "omni" capabilities, our data infrastructure must be unbreakable. We are looking for a Data Reliability Engineer who brings a Site Reliability Engineering (SRE) mindset to the world of massive-scale data. You will be responsible for the resilience, automation, and scalability of the petabyte-scale pipelines that feed our research. This is not just about keeping the lights on; it’s about treating infrastructure as code and building self-healing data systems that allow our researchers to train on massive datasets without interruption. Whether you are a junior engineer with a passion for automation or a seasoned SRE veteran, you will play a critical role in hardening the backbone of Luma’s intelligence.
What You'll Do
- Automate Everything: Apply Infrastructure-as-Code (IaC) principles using Terraform to provision, manage, and scale our data infrastructure.
- Harden Data Pipelines: Build reliability and fault tolerance into our core data ingestion and processing workflows, ensuring high availability for research jobs.
- Scale Kubernetes & Ray: Operate and optimize large-scale Kubernetes clusters and Ray deployments to handle bursty, high-throughput workloads.
- Define Reliability: Establish Service Level Objectives (SLOs) and observability standards (Prometheus/Grafana) for our data platforms.
- Debug & Heal: serve as the first line of defense for complex infrastructure failures, diagnosing root causes in distributed storage and compute systems.
Who You Are
- Deep SRE/DevOps proficiency: You live and breathe Linux, networking, and automation.
- Infrastructure-as-Code Native: You have extensive experience with Terraform, Ansible, or similar tools to manage complex cloud environments (AWS/GCP).
- Kubernetes Expert: You have managed Kubernetes in production and understand its internals, not just how to deploy containers.
- Python Proficiency: You can write high-quality Python code for automation, tooling, and infrastructure management.
- Data-Minded: You understand the specific challenges of stateful data systems and high-throughput storage (S3/Object Store).
What Sets You Apart (Bonus Points)
- Experience managing GPU clusters or AI/ML workloads.
- Background in both Software Engineering and Operations (DevOps).
- Experience with high-performance networking (InfiniBand/RDMA).
The base pay range for this role is $170,000 – $360,000 per year.
About LumaLuma’s mission is to build unified general intelligence that can generate, understand, and operate in the physical world.
We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable and useful systems, the next step function change will come from vision. So, we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.
Skills Required
- Extensive experience with Terraform, Ansible or similar tools
- Experience managing production Kubernetes
- High-quality Python coding for automation
- Deep SRE/DevOps proficiency in Linux and networking
- Experience with stateful data systems and high-throughput storage
Luma AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Luma AI and has not been reviewed or approved by Luma AI.
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Fair & Transparent Compensation — Pay is considered competitive for senior technical and some non-technical roles, with posted bands indicating strong market alignment in key locations. Publicly listed ranges provide directional clarity for certain roles and markets.
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Equity Value & Accessibility — Equity is positioned as a meaningful component of total compensation, and language in postings emphasizes ownership alongside cash pay. Signals indicate equity can be significant in senior roles where competition for talent is intense.
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Healthcare Strength — Core medical, dental, and vision coverage are referenced in multiple postings, aligning with standard expectations for venture-backed tech companies. These inclusions suggest baseline health benefits are part of the package.
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The Company
What We Do
Luma AI’s mission is to build Multimodal AGI: AI that can generate, understand, and operate in the physical world. We develop multimodal models across video, 3D, and generative media, and ship them in products like Dream Machine to help creators and teams turn ideas into compelling visuals—fast.
