About Us
We build high-performance foundation models designed to run efficiently across a wide range of environments—from edge devices to large-scale deployments. Our work spans models from ~1B to 100B+ parameters across LLMs, diffusion models, and other modalities, with a strong focus on scalable training, efficient inference, and real-world deployment.
Our Bonsai family of 1-bit and ternary models is designed to dramatically improve the efficiency of modern AI systems, enabling advanced intelligence to run with significantly lower memory usage, latency, and energy consumption across cloud and edge environments.
Role Overview
We are seeking an experienced part-time AI/ML engineer to lead developer relations efforts for Bonsai models and related platform technologies. This role focuses on helping developers understand, adopt, and build with our models through technical content, demos, tutorials, social media engagement, and community building.
You will act as a bridge between engineering and the developer community, creating compelling examples and educational resources that showcase the capabilities of highly efficient 1-bit and ternary AI systems. This role is initially part-time with the potential to grow into a full-time position as the developer ecosystem expands.
Responsibilities
You will create technical content and developer experiences that drive adoption and engagement across the AI/ML community. Core responsibilities include:
- Building demos, sample applications, notebooks, and reference implementations using Bonsai models
- Creating tutorials, technical guides, videos, blog posts, and other developer-focused educational content
- Developing example workflows for inference, fine-tuning, evaluation, and deployment across different hardware and runtimes
- Engaging with developers across social media, GitHub, Discord, X/Twitter, Reddit, YouTube, and other technical communities
- Showcasing new capabilities, benchmarks, and product releases through compelling technical storytelling
- Gathering feedback from developers and communicating ecosystem needs back to engineering and product teams
- Supporting hackathons, workshops, community events, design partners, and developer onboarding efforts
- Helping establish best practices and documentation for building with Bonsai models and platform APIs
Basic Qualifications
You bring strong technical communication skills alongside hands-on AI/ML engineering experience:
- 2–3+ years of experience in AI/ML engineering, developer relations, technical evangelism, or related fields
- Strong programming skills in Python and experience building AI/ML applications
- Hands-on experience working with LLMs, inference systems, or modern AI frameworks
- Proven ability to create high-quality technical content and developer-facing educational material
- Active presence in developer communities or social media platforms with demonstrated audience engagement
- Strong communication and presentation skills across written, video, and live formats
- Ability to work independently and balance technical depth with accessibility
Preferred Qualifications
You have additional experience aligned with developer ecosystems and AI infrastructure platforms:
- Experience building demos or educational content for AI/ML infrastructure, inference systems, or open-source frameworks
- Familiarity with model serving frameworks and runtimes such as llama.cpp, vLLM, TensorRT, MLX, or similar systems
- Experience creating technical video content, livestreams, workshops, or conference presentations
- Existing audience or following within AI/ML, open-source, or developer communities
- Experience managing developer communities, open-source programs, or technical partnerships
- Familiarity with edge AI, quantized models, or efficient inference systems
- Contributions to open-source AI/ML projects or developer tooling
Ideal Candidate Profile
You enjoy helping developers discover and build with new technologies, and you know how to make complex systems approachable and exciting. You are equally comfortable writing code, creating tutorials, recording demos, engaging on social media, and interacting directly with developers. You understand what makes developers adopt new tools, have strong instincts for technical storytelling, and thrive at the intersection of AI engineering, community, and product adoption.
