Member of Technical Staff

📋 Job Overview

At Avra, every technical IC is a Member of Technical Staff (MTS). The title doesn't put anyone in a silo: you own systems and outcomes, not steps in a function, and you keep building depth in your area. Seniority shows up in your scope, level, and compensation, not in titles. In this role, you'll join the Platform team to own where our models execute. Customers consume our models through large batches of millions of records and through real-time APIs, and they make business decisions on every response. You'll run governed model releases reliably and efficiently — in our cloud and on customer-hosted Kubernetes — and make inference fast, predictable, and cheap enough to serve both enterprise and mid-market customers.

🏢 About Avra

Avra is a company focused on building inference platforms that enable customers to make business decisions based on model outputs. The company emphasizes technical ownership and depth in specialized areas.

🎯 The Role

You will join the Platform team to own where our models execute. This involves running governed model releases reliably and efficiently, both in our cloud and on customer-hosted Kubernetes. The goal is to make inference fast, predictable, and cost-effective for enterprise and mid-market customers.

✅ Key Responsibilities

• Evolve Sophos, our online and batch inference runtime, built on Kubernetes.
• Run large batch inference on ephemeral jobs, with multi-dimensional admission control (CPU, memory, GPU) through Kueue.
• Build and extend the Sophos controller and its Kubernetes custom resources.
• Optimize each model's inference engine and feature processing, using vectorized, columnar operations.
• Serve graphs and data efficiently from Lance-based storage.
• Own execution of training, post-training, and fine-tuning jobs, in our cloud and in customer dataplanes.
• Drive autoscaling, GPU serving, performance, and cost optimization, with telemetry for every model we run.
• Solve open problems such as deterministic job sizing, checkpointing and recovery for batch runs, per-customer encryption and isolation, resilience to difficult input files, and automatic profiling when a new model is accepted.

📌 Required Qualifications

• Experience running model serving or large-scale batch compute on Kubernetes.
• Experience building Kubernetes controllers or operators.
• Skill at profiling and optimizing data-heavy Python pipelines.
• A clear sense of cost: you treat compute efficiency as a product feature.
• Production-quality code and reviews, and a willingness to operate what you build.

⭐ Desirable Experience

• Ray, Ray Serve, or KubeRay in production.
• Kueue or other batch scheduling and admission-control systems.
• GPU serving and performance optimization.
• Arrow, Parquet, Lance, or other columnar formats.
• Shipping software to customer-hosted Kubernetes.
• GCP/AWS and GKE/EKS, and financial services or regulated environments.

🎁 Benefits

Competitive compensation package, including salary, benefits, and opportunities for growth within the company.

🛂 Visa & Eligibility

No specific visa or eligibility information provided.