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# Machine Learning Engineer, Model Integrations

- **Company:** Nunchaku AI, Inc.
- **Location:** San Francisco, CA, United States
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Software Debugging, Python (Programming Language), Machine Learning, Open Source Technology, Systems Integration, Pytorch, Snowflake, Adobe, HuggingFace, ComfyUI (Graph-based Pipeline Editor for Generative Image Workflows), SGLang, Machine Learning Operations, Api Management
- **Published:** November 9, 2026
- **Apply:** https://www.juju.com/job/28_25197_6ec7e2da8e151cde646771902dd1c467

## About the Role

* Python and PyTorch: Strong in both, and comfortable reading model code, adapting inference pipelines, and debugging model behavior.
 * Production systems experience: You have deployed a model or built an API integration. Comfortable working with existing serving tools, reading logs, and debugging failed requests.
 * Working style: Quick to learn unfamiliar model code and get a prototype working. Able to keep the first release focused, resolve launch blockers, and coordinate with teammates to ship., * Experience with Hugging Face, Diffusers, ComfyUI, or model-serving frameworks such as SGLang or vLLM.
 * Experience working with external model providers, or building a multi-model API platform.
 * Contributions to open-source ML or inference projects.

## Description

Help Nunchux bring new image and video models to Modelverse as soon as they become available. Your focus is speed to launch: get the model running, connect it to the platform, and ship a working first version., * Prototype new models: Get new image and video models running quickly with the available code and weights. Run test examples and identify what each model needs for launch.

 * Ship the first version: Coordinate the deployment with the cloud team, and the API and Modelverse integration with the product engineers. Get the basic parameters, examples, and developer instructions ready for Day 1.
 * Speed up the launch process: Find bottlenecks, automate manual steps, and simplify the handoffs with the cloud and product teams. Build reusable adapters and launch scripts to reduce the work each new model takes.
 * Verify and hand off: Test the integration end to end, including the outputs and the error handling. Fix launch blockers, and document the known limitations for the teams that take on further optimization.
 * Maintain the integration platform: Between launches, fix bugs and add support for new model interfaces, providers, and modalities in our shared integration and serving code., * Image or video model experience: You have run and adapted generation models, or integrated provider APIs., * Own model launches: Take new models from their first run to a release developers can use on Modelverse.
 * Work with new models: Get hands-on with image and video models as they ship, across providers and architectures.
 * Proven traction: Build on open-source work with more than 4 million model downloads, and on growing industry partnerships.
 * The team: Work with researchers from MIT, Berkeley, and CMU, and with industry veterans from NVIDIA, AMD, Snowflake, and Adobe.