ML Engineer
Added
4/18/2026
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Note: We've kept the name of the company private. If you'd like to know the company before requesting an intro, just email us at hello [at] fractionaljobs.io
About Us
We’re building an AI-assisted ESL learning platform that combines explicit, rule-based grammar analysis with modern AI to help learners better understand and apply English.
We’re an early-stage, self-funded company with a commitment to encoding syntactic representation. Our founder who has over 10 years of experience as an IT PM, teaching English overseas, and developing the underlying language methodology and syntax mapping.
About the Work
We're getting started on our MVP now, but don't yet have the proper ML expertise in-house. We're looking for a fractional ML Engineer to own the AI tutor model from development through deployment.
Specifically, you'll:
- Fine-tune an LLM to deliver grammar explanations aligned with a proprietary language framework
- Build a RAG system using our proprietary framework documentation as the knowledge base
- Design and implement an evaluation harness and regression testing pipeline to validate model quality
- Own the full ML pipeline from data preparation through production deployment
- Work most closely with the founder, the small eng team, and a Fractional CTO (also hired through Fractional Jobs)
About You
You MUST have:
- Significant experience fine-tuning LLMs, deploying it to production, and iterating/improving on it
- Built RAG systems for production use
- Worked specifically in NLP ML (grammar, language learning, text analysis, etc.)
- If your ML experience does not include any NLP, we won't be the right fit
- Can be based anywhere in the world, with a preference for folks in UK, Europe, and Asia time zones
Nice-to-haves:
- Experience with language learning products specifically
How to Get in Touch
Hit that "Request Intro" button below. Include any relevant links so we can get to know you better.
Your brief intro note should clearly address:
- The tech companies you've done ML engineering work for, and a bit about what that work looked like
- Your specific experience fine-tuning LLMs, building RAG systems, and deploying them to production
- Examples of your NLP and language-specific work
If we think there's a fit, we'll reach out to schedule an intro call. Looking forward!
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