LLM Fine-Tuning and Alignment Engineer - Content Developers

Status
Open
Remote policy
Remote
Employment type
Not stated
Salary
Not stated
Categories
LLM-Fine-Tuning-Engineer, AI-Engineer, AI-ML-Developer, AI-Systems-Engineering, Machine-Learning-Engineer, AI-LLM-Engineer, LLM-Engineer, LLM-Optimization-Specialist, AI-Content-Engineering, AI-LLM-Engineering
Tech
remote-countryml
Source
himalayas
First observed
2026-09-18 20:13 UTC
Last seen
2026-09-18 20:13 UTC
Source claims posted
2026-09-18 20:04 UTC
Consecutive misses
0 of 10

What the posting says

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.

Requirements

We're looking for a content developers for its Master in AI Systems Engineering.

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.

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.

Benefits

Remote work modality (home office).

Joining a dynamic and growing organization with international reach.

Originally posted on Himalayas

Quality

Completeness: 65%

Not enough history yet to judge honesty signals.

Timeline

  1. *
    #845183 2026-09-18 20:13 UTC
    Published