---
title: 'AI Researcher — Distillation at Featherless AI'
canonical: 'https://feeny.ai/job/ai-researcher-distillation-featherless-ai-remote-zxs1tx4mwq1f'
type: 'job'
last_seen: '2026-09-15'
---

# AI Researcher — Distillation at Featherless AI

- **Company:** Featherless AI
- **Location:** Remote
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-01-23
- **Last confirmed live:** 2026-09-15
- **Apply:** https://jobs.ashbyhq.com/featherlessai/46d1ece5-b24f-419c-8845-b696797c7ae6

## Job description

## About the Role

We’re looking for an AI Researcher focused on model distillation to help us push the frontier of efficient, high-performance models. You’ll work on turning large, expensive models into smaller, faster, and more deployable systems—while maintaining or improving quality. This role is ideal for someone who enjoys publishing research, working close to real systems, and seeing their ideas move from papers → code → production.

## What You’ll Work On

- Design and evaluate model distillation techniques (teacher–student training, self-distillation, layer-wise distillation, representation matching, etc.)
- Research tradeoffs between model size, latency, memory, and accuracy
- Develop novel distillation approaches for:
- Large language models
- Long-context or specialized architectures
- Inference-constrained environments
- Run large-scale experiments and ablations; analyze results rigorously
- Collaborate with engineers to productionize research outcomes
- Write and submit research papers to top-tier venues (NeurIPS, ICML, ICLR, COLM, etc.)
- Contribute to internal research notes, technical blogs, and open-source projects when appropriate

## What We’re Looking For

Required

- Strong background in machine learning research
- Hands-on experience with model distillation or closely related topics (compression, pruning, quantization, representation learning)
- Publication experience (conference or journal papers, workshop papers, or arXiv preprints)
- Solid understanding of deep learning fundamentals (optimization, training dynamics, generalization)
- Fluency in PyTorch (or equivalent) and research-grade experimentation
- Ability to clearly communicate research ideas, results, and limitations

## Nice to Have

- Experience distilling large language models
- Work on efficiency-focused research (latency, memory, throughput)
- Experience with long-context models or non-Transformer architectures
- Open-source contributions in ML or research tooling
- Prior startup or applied research experience

## Why Join Us

- Real ownership over research direction at a Series A stage
- Strong support for publishing and open research
- Tight feedback loop between research and real-world deployment
- Access to meaningful compute and production-scale problems
- Small, highly technical team with deep ML and systems expertise

Example Backgrounds

- ML researchers from academia transitioning to industry
- Research engineers with published work in model efficiency
- PhD / Post-doc graduates or industry researchers who still want to publish

## About Featherless AI

## Company Overview
- **One-liner**: Featherless AI provides a serverless platform that offers API access to over 40,000 open-weight AI models from a single endpoint, designed for developers and enterprises.
- **Entity Type**: Private (Series A)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2023
- **Founders**: Eugene Cheah (CEO, Co-Founder)

## Core Business
- **Primary industry**: Artificial Intelligence Infrastructure / Serverless LLM Hosting
- **Target customers**: B2B, serving developers, AI startups, and enterprises seeking scalable, cost-effective inference for open-source models.
- **Mission or purpose**: To democratize access to all AI models by making them available for serverless inference, eliminating the need for server setup and complex infrastructure management.

## Products & Services
- **Featherless API**: A unified API gateway providing instant access to over 40,000 open-weight models (e.g., DeepSeek, Llama, Mistral, Qwen, RWKV, GLM, Kimi) without setup or hosting. Pricing is flat-rate with unlimited tokens, starting at $25/month for up to 4 concurrent connections and 32K context, scaling to $200/month for higher tiers. Agent-specific plans ($100/month) include sandbox environments and persistent storage. The service emphasizes low latency, dependable uptime, and predictable costs.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: **Total Funding of $25M** — raised $5M in a Seed round (April 2025, led by Airbus Ventures) and $20M in a Series A round (announced ~May 2026, details still emerging).
- **Notable Investors/Partners**: Airbus Ventures, Kickstart Ventures, Panache Ventures, BMW i Ventures, AMD Ventures, and 11 other investors. The platform is built by researchers contributing to RWKV, a Linux Foundation project.
- **Growth Signals**: The company is on a rapid growth trajectory, with headcount increasing 46.7% year-over-year to 14 employees. The website boasts over 2,100 "stars" for its Discord community. The company has a global presence, operating in 9 countries (including Singapore, Canada, Czechia, UK, Belgium, and Sweden). Website traffic is strong (73,508 monthly visits, growing +19.9% month-over-month), and there are 43 active job postings, a 65.4% quarterly increase in hiring. The Series A announcement signals significant investor confidence.

## Competitive Advantages
- **Extensive Model Library & Zero-Friction Access**: A single API key provides access to the entire Hugging Face trending library, including models up to 229B parameters, with no need to manage infrastructure.
- **Unlimited-Token, Flat-Rate Pricing**: A strong differentiator in the "per-token" pricing era, offering predictable costs suitable for scaling, with tiers from $25 to $200/month.
- **Build for Reliability & Performance**: Architecture designed for real workloads with low latency and dependable uptime, utilizing proprietary GPU orchestration and model load-balancing.
- **Open-Source Roots & Community**: Built by researchers contributing to RWKV (a Linux Foundation project), the company is deeply embedded in the open-source AI ecosystem, which fosters trust and community-driven development.

## Strategic Focus
- **Scaling the Platform & Enterprise Adoption**: The Series A funding will be used to expand AI infrastructure and grow the platform. The company is actively hiring for senior roles like Founding Account Executives and Business Development Reps, signaling a shift toward aggressive go-to-market and enterprise sales.
- **Expanding Global Presence**: With a distributed team across the US, Europe, and Asia, the company is building a global, remote-first workforce.
- **Technical Innovation**: Focused on continuous improvement of inference performance and cost-efficiency through their GPU orchestration system and model load-balancing.

## Why Work Here
- **High-Growth Stage**: As a Series A startup with strong investor backing, this is an opportunity to join a company experiencing rapid scaling, which offers significant career growth and impact potential.
- **Impact & Ownership**: Employees are likely to have high autonomy and a direct impact on the company's trajectory, from building core infrastructure to driving revenue.
- **Remote-First & Global Team**: Based on the distributed headcount across 9 countries (US, Singapore, Canada, UK, Belgium, etc.), the company is clearly remote-first, offering flexibility in where you work. Job postings reflect opportunities in the US and Europe (e.g., Paris, Berlin).
- **Cutting-Edge Technical Challenge**: The core work involves solving complex problems in AI inference, GPU orchestration, and MLOps, making it a compelling place for engineers and researchers passionate about AI infrastructure.
- **Culture & Values**: The company's deep ties to open-source AI communities and its "flat-rate, no-surprises" pricing philosophy likely translate into a transparent, developer-friendly internal culture. The small, highly-skilled team (14 people) suggests a close-knit, high-performing environment.

## Sources
1. [Featherless.ai Website](https://featherless.ai/)
2. [Featherless AI LinkedIn](https://www.linkedin.com/company/feather-serverless-ai)
3. [Featherless AI Docs](https://featherless.ai/docs/overview)
4. [CB Insights Profile](https://www.cbinsights.com/company/recursal-ai)
5. [Featherless AI Jobs](https://jobs.ashbyhq.com/featherlessai)

## Other roles at Featherless AI

- [Founding Sales Engineer](https://feeny.ai/job/founding-sales-engineer-featherless-ai-us-bfj59k5ej0kf) — US &, Canada
- [Founding Business Development Rep (AI Cloud US/CA)](https://feeny.ai/job/founding-business-development-rep-ai-cloud-us-ca-featherless-ai-us-973psexhmg2e) — US &, Canada
- [Founding Account Executive (AI Cloud)](https://feeny.ai/job/founding-account-executive-ai-cloud-featherless-ai-us-wb7s9fy8rf34) — US &, Canada
- [Chief of Staff](https://feeny.ai/job/chief-of-staff-featherless-ai-san-francisco-15ydsmveqwsq) — San Francisco, CA
- [Content Marketer](https://feeny.ai/job/content-marketer-featherless-ai-europe-xnsbz1evvkbs) — Europe
- [Business Development Rep (AI Cloud)](https://feeny.ai/job/business-development-rep-ai-cloud-featherless-ai-europe-hd5fymsqsh5h) — Europe
- [AI Researcher — Training Optimization](https://feeny.ai/job/ai-researcher-training-optimization-featherless-ai-remote-hyc2csn67p2p)
- [AI Researcher – Multilingual Data](https://feeny.ai/job/ai-researcher-multilingual-data-featherless-ai-remote-aj24t2jw442p)
- [AI Researcher — AI Architecture Research](https://feeny.ai/job/ai-researcher-ai-architecture-research-featherless-ai-remote-dprg8203nt10)
- [AI Researcher — Inference Optimization](https://feeny.ai/job/ai-researcher-inference-optimization-featherless-ai-remote-5q35t4rfgjve)