Founding AI Engineer, Model & Inference
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Key skills for this role
About the Role
WYLE is building a Personal Operating System and seeks a Founding AI Engineer to own model training, quantization, and self-hosted inference. The role requires hands-on experience fine-tuning models, quantizing with intent, and running production inference.
Key Skills for This Role
Responsibilities
- Own the model and inference work end to end, building toward smaller, faster models run in house
- Fine tune, quantize, and serve models in production
- Optimize accuracy versus latency trade offs
- Work directly with the founder as a horizontal engineering owner
Requirements
- Have fine tuned real models (SFT, LoRA or QLoRA, preference tuning) and can show the result
- Quantize with intent (GPTQ, AWQ, GGUF, FP8) and own the accuracy versus latency trade off
- Have run self hosted inference in production (vLLM, TGI, SGLang, or Triton) and made it faster or cheaper
- Own the full loop from data to training to quantization to serving
- Dubai based or ready to relocate quickly
Full Job Posting
About WYLE
- At WYLE, we are building an AI that runs the parts of your life you should not have to think about, so you get your time and attention back.
- Not another app. A Personal Operating System for people whose lives are too full to manage by hand.
- It has to work reliably in one real person's life, over years, in the actual mess of a real day. That is a hard engineering problem before it is anything else.
- This role owns one part of it: WYLE will not stay a wrapper around someone else's models. We are building toward smaller, faster models we run ourselves. You own that work, end to end.
You are a fit only if:
- You have fine tuned real models (SFT, LoRA or QLoRA, preference tuning) and can show the result. Inspectable weights, benchmarks, or an eval someone can check. If you have never shipped a model another engineer could look at, this is not your role.
- You quantize with intent (GPTQ, AWQ, GGUF, FP8) and own the accuracy versus latency trade off rather than guessing at it.
- You have run self hosted inference in production (vLLM, TGI, SGLang, or Triton), made it faster or cheaper, and can explain exactly how.
- You own the full loop, from data to training to quantization to serving. You are not a research scientist who hands off a checkpoint, and your AI experience is not just calling an API.
- Bonus: on device or edge inference, distillation, and low latency on ordinary consumer hardware.
How we work
- Engineering is horizontal on purpose. You work directly with the founder, everyone owns something real, and there are no layers between you and the decisions.
- This is for someone who has built inside a startup before and wants that again as an owner, not an employee.
- If you are a Head of Engineering, Director, Head of AI, Principal or Staff Engineer and what you miss is your hands on the keyboard owning what you build, this is for you. If you want another management seat, this is not.
The honest part
- This is a founding role, equity led with a partial salary for the founding team that steps up as our funding closes and moves to full market salary at the raise.
- We are direct about the full structure early, not after your time is spent.
- If you want a salary first role with a big team around you, that is fair, and this is not it.
- Dubai based, or ready to relocate quickly. We provide the visa and support the move.
To apply
- We read every application by hand, and this role is built so an auto apply agent cannot do it well.
- Do not use LinkedIn Easy Apply. Email ceo@wyle.ai, tell us Model and Inference is your domain, and point us at something you built that proves it: a model you trained, code, an open source project.
- Open with the hardest reliability or correctness failure you have owned in production and how you found it.
- Applications that open with a resume summary or a generic pitch, we pass on. We would rather see the work.
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