Lead Software Engineer, Model Serving Platform

🕒 April 12

🏢🏡 San Francisco – Hybrid

💵 $230k - $300k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 65%

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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Sciforium

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2024

🤖 Artificial Intelligence

🔌 API

🔧 Hardware

🔥 Funding within the last year

💰 $12M Seed Round - Sciforium on 2025-10

Artificial Intelligence • API • Hardware

Sciforium is a serverless AI infrastructure platform that provides production-ready, multimodal AI services via a unified, OpenAI-compatible API. The company runs vertically integrated AMD GPU hardware and offers model hosting, a model library, real-time evaluation pipelines, and managed agent deployments to help teams build, evaluate, and ship text, image, video, and audio AI applications with lower cost, stronger privacy, and predictable performance.

📋 Description

• Lead the technical direction of the model serving platform, owning architecture decisions and guiding engineering execution. • Build core serving components including execution runtimes, batching, scheduling, and distributed inference systems. • Develop high-performance C++ and CUDA/HIP modules, including custom GPU kernels and memory-optimized runtimes. • Collaborate with ML researchers to productionize new multimodal models and ensure low-latency, scalable inference. • Build Python APIs and services that expose model capabilities to downstream applications. • Mentor and support other engineers through code reviews, design discussions, and hands-on technical guidance. • Drive performance profiling, benchmarking, and observability across the inference stack. • Ensure high reliability and maintainability through testing, monitoring, and engineering best practices. • Troubleshoot and resolve complex issues across GPU, runtime, and service layers.

🎯 Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience • 5+ years of experience designing and building scalable, reliable backend systems or distributed infrastructure • Strong understanding of LLM inference mechanics (prefill vs decode, batching, KV cache) • Experience with Kubernetes/Ray, Containerization • Strong proficiency in C++, Python • Strong debugging, profiling, and performance optimization skills at the system level • Ability to collaborate closely with ML researchers and translate model or runtime requirements into production-grade systems • Effective communication skills and the ability to lead technical discussions, mentor engineers, and drive engineering quality • Comfortable working from the office and contributing to a fast-moving, high-ownership team culture.

🏖️ Benefits

• Medical, dental, and vision insurance • 401k plan • Daily lunch, snacks, and beverages • Flexible time off • Competitive salary and equity