Academic Content Developer - LLM Fine-Tuning and Alignment Engineer
Why This Role Stands Out
This remote role offers you a unique opportunity to shape the future of AI education and contribute to a mission of economic transformation, leveraging your expertise in LLM fine-tuning and alignment. You'll thrive here if you have a strong production AI/ML background and a passion for creating high-quality technical content. Join a dynamic, growing international organization and make a significant impact.
Quick Overview
Job Description
Jala University is an innovative initiative designed to bridge the gap between academia and industry by delivering practical education tailored to industry needs, with a unique educational model integrating experts from both academia and industry.
Our goal is to transform the economies of underserved regions through the software industry, creating professional opportunities that impact individuals, communities, and regions, while leaving a lasting legacy for future generations.
We're looking for a content developers for its Master in AI Systems Engineering. . You'll design module content, labs, a reference implementation, an evaluation harness, and an instructor guide.
A tuned model plus an audit report, covering SFT, PEFT/LoRA, DPO/KTO, verifier-driven RL, domain-data preparation, preference optimization, and alignment-auditing methodology — plus module content, labs, an evaluation rubric, and an instructor guide.
- Masters Degree in Computer Science or related.
- 5+ years shipping production software, 2+ years in production AI/ML.
- Production SFT, PEFT and preference-optimization experience on real domain data.
- An alignment-audit track record.
- Comfortable at multi-GPU scale, disciplined about run lineage
- Can build the artifact personally, to production standard.
- Public writing samples showing technical explanation (docs, workshop material, book chapter, or open-source project known for its docs), including ability to write to publication standard
- Reproducibility discipline (pinned dependencies, containers, seeded runs, documented decoding parameters)
- Professional written English
Tech stack: Axolotl, Unsloth, PEFT, TRL, Hugging Face Inference Endpoints, Modal (H100 / A100 80GB), Weights & Biases, OpenRouter.
- Remote work modality (home office).
- Joining a dynamic and growing organization with international reach.