---
title: 'Founding Engineer, AI Infra at Cox Exponential'
canonical: 'https://feeny.ai/job/founding-engineer-ai-infra-cox-exponential-san-francisco-bay-area-fx5arytyxdwv'
type: 'job'
last_seen: '2026-09-05'
---

# Founding Engineer, AI Infra at Cox Exponential

- **Company:** Cox Exponential
- **Location:** San Francisco Bay Area, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-06-11
- **Last confirmed live:** 2026-09-05
- **Apply:** https://jobs.gem.com/cox-exponential/am9icG9zdDqPHlWla9k8DERT7WdX4Oke

## Job description

## About Goaly

At Goaly, our mission is to make custom AI affordable for every business. Our founding team comes from the front lines of top AI labs and tech giants (Meta MSL, TikTok AI, Google DeepMind, xAI, Microsoft Research, etc.), where we built large-scale training infrastructure powering trillion-parameter models and scaled GenAI models to a global user base. Now, we are building something we wish we had before: a platform that makes training and adapting custom AI affordable for all modern companies, not just Big Tech. Our north star is ambitious: for a domain-specific task, reach 90% of SOTA performance at less than 10% of the cost. To get a taste of what we are doing, see our [first tech blog](https://www.goaly.ai/blog).

## About the Role

You will sit at the intersection of systems engineering and applied ML, building specialized infrastructure that keeps large language and multimodal models fast, reliable, and cost-effective. You will partner with research, product, and infra teams to ship production-ready platforms for training and serving AI at scale.

## Key Responsibilities

- Efficiency & performance: Improve LLM training and inference efficiency through better memory utilization, optimized parallelism, and kernel-level innovations (e.g. FlashAttention, CUDA/Triton).
- Training & RL robustness: Build scalable, stable training and RL pipelines with strong reproducibility, observability, and debuggability.
- Serving & inference optimization: Design and tune high-throughput, low-latency model serving systems, including quantization, caching, and speculative decoding.
- Scalability & infrastructure: Own end-to-end training and inference infrastructure — from data ingestion and checkpointing to multi-GPU and multi-cloud orchestration.
- Production enablement: Work closely with researchers and product engineers to turn new algorithms into reliable, production-ready systems.

## Requirements

- 5+ years building or operating ML infrastructure at scale, ideally supporting large language or multimodal models.
- Deep understanding of GPU architecture, distributed training frameworks (PyTorch, DeepSpeed, Megatron, Ray), and parallelism strategies.
- Hands-on experience running inference stacks (vLLM / SGLang, TGI, Triton) and optimizing them via low-level profiling.
- Strong software engineering fundamentals in Python and one of C++/Rust/Go, with clean, reliable code shipped to production.
- Working knowledge of modern data pipelines, feature stores, and vector databases used in production AI systems.
- Comfort automating infrastructure with Kubernetes, Terraform/Pulumi, and observability stacks (Prometheus, Grafana, OpenTelemetry).

Bonus Points

- Experience deploying open-source LLMs (Llama 3, Qwen, DeepSeek) or training custom foundation models.
- Contributions to ML systems tooling (compilers, kernels, inference runtimes) or open-source infrastructure projects.
- Background in reinforcement learning, evaluation harnesses, or alignment tooling that hardens production AI systems.

## About Cox Exponential

## Company Overview
- **One-liner**: Cox Exponential (CX2) is the early-stage AI venture vehicle for Cox Enterprises, partnering with exceptional entrepreneurs to build breakthrough AI/ML companies.
- **Entity Type**: Private (venture capital / accelerator; part of Cox Enterprises)
- **Headquarters**: Silicon Valley, California, United States (with remote presence and an international outlook)
- **Founded**: 2025
- **Founders**: Founded by technologists with decades of experience leading startups and building AI/ML products; key executives include Managing Partner Radu B. Rusu, General Partners Pantelis Kalogiros, Yukiko Jenkins, and others.

## Core Business
- **Primary industry**: Venture Capital & Private Equity (AI-focused early-stage investing)
- **Target customers**: B2B – exceptional entrepreneurs and early-stage AI companies seeking capital, mentorship, and access to the Cox family of businesses.
- **Mission**: Develop breakthrough technology that helps people flourish and bring firsts to market.

## Products & Services
Cox Exponential does not sell a product; it operates as an investment vehicle. Its main “offering” is its accelerator program and venture partnership:
- **AI Accelerator & Venture Program**: Provides capital, technical mentorship, business planning, code/prototype development, and connection to the Cox Enterprises ecosystem.
- **Portfolio Support**: Invests in and supports portfolio companies such as Spacer Robotics (autonomous rebar-tying robot), TrustMind, TrustFoundry.ai, and others.

## Market Standing
- **Valuation / Funding**: Not publicly disclosed (backed by Cox Enterprises, a large private conglomerate).
- **Key Metric**: Total employees ~20 (as of mid-2026); headcount grew ~144% year-over-year since founding in 2025.
- **Notable Investors / Partners**: Cox Enterprises (parent); key executives from Scale Venture Partners, Fyusion, AGI House, etc.
- **Growth Signals**: Rapid team expansion, active hiring for senior engineering roles (AI infra, robotics, efficient ML), multiple open remote positions.

## Competitive Advantages
- **Cox Enterprises Backing**: Access to the breadth of a Fortune 500 company’s resources, industry connections, and potential pilot customers.
- **Founder-Led by Technologists**: The team comprises experienced AI/ML startup builders, offering hands-on technical guidance to portfolio companies.
- **Global Outlook**: Based in Silicon Valley with an international perspective, attracting talent from the US and Portugal.
- **Early-Stage Focus**: Dedicated to pre-seed and seed AI startups, differentiating from larger, less specialized corporate venture arms.

## Strategic Focus
- **Current priorities**: Scaling the accelerator, expanding portfolio companies, and building in-house AI infrastructure talent to support portfolio needs.
- **Direction for growth**: Deepening ties with Cox business units, investing in frontier AI (LLMs, multimodal models, agentic RL, robotics), and hiring top-tier engineers to work on internal AI platforms and portfolio support.

## Why Work Here
- **Culture**: Early-stage, high-autonomy environment within a stable corporate parent. Employees work on cutting-edge AI challenges across multiple portfolio companies.
- **Remote/Hybrid**: Fully remote workspaces for many roles; some positions require in-office presence in San Francisco (e.g., robotics roles). The company has 8 locations but emphasizes remote flexibility.
- **Notable Perks**: Opportunity to work on diverse AI/ML projects (LLMs, robotics, efficient ML systems), exposure to multiple startups, and a flat hierarchy with direct access to experienced partners.
- **Engineering Culture**: Strong emphasis on technical excellence, with open roles for Founding Engineer (AI Infra), Research Scientist (Efficient ML), Robotics Software Engineer, and Systems Engineer.

## Sources
1. [LinkedIn – Exponential by Cox](https://linkedin.com/company/exponential-by-cox)
2. [Built In – Cox Exponential](https://builtin.com/company/cox-exponential)
3. [Built In – Cox Exponential Jobs](https://builtin.com/company/cox-exponential/jobs)
4. [The Org – Cox Exponential (CX2)](https://theorg.com/org/cox-exponential-cx2)
5. [RemoteFront – Remote Jobs at Cox Exponential](https://www.remotefront.com/companies/Cox%20Exponential)

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