Member of Technical Staff – Inference Platform

Job not on LinkedIn

🕒 September 23

🇧🇷 Brazil – Remote

⏰ Full Time

🔴 Lead

🖥 Software Engineer

👻 Ghost score 12%

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avra

WebsiteLinkedInAll Job Openings

1 - 10 employees

💼 Consulting

💸 Finance

🤝 B2B

Consulting • Finance • B2B

Avra is a venture capital firm dedicated to empowering growth stage founders by providing the essential support needed to scale their companies after Series A funding. With a commitment to building a prosperous future together, Avra focuses on strategic investments that foster innovation and entrepreneurship.

📋 Description

• Own execution environments for models on the Platform team • Evolve Sophos, the online and batch inference runtime built on Kubernetes • Run large batch inference on ephemeral jobs using multi-dimensional admission control through Kueue • Build and extend the Sophos controller and Kubernetes custom resources • Optimize model inference engines and feature processing using vectorized, columnar operations • Serve graphs and data efficiently from Lance-based storage • Own training, post-training, and fine-tuning jobs in Avra's cloud and customer dataplanes • Drive autoscaling, GPU serving, performance, and cost optimization with telemetry for every model • Solve deterministic job sizing, checkpointing and recovery, customer encryption and isolation, input-file resilience, and automatic profiling • Achieve 99.9% serving availability, low online-inference latency, high batch throughput, optimized costs, GPU utilization, and reliable job completion

🎯 Requirements

• 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 • Clear sense of cost and compute efficiency • Production-quality code and code review experience • Willingness to operate what you build • Nice-to-have: Ray, Ray Serve, or KubeRay in production • Nice-to-have: Kueue or other batch scheduling and admission-control systems • Nice-to-have: GPU serving and performance optimization • Nice-to-have: Arrow, Parquet, Lance, or other columnar formats • Nice-to-have: Shipping software to customer-hosted Kubernetes • Nice-to-have: GCP/AWS, GKE/EKS, and experience in financial services or regulated environments

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