Academic Content Developer - ML Platform and Inference Engineer
Jalasoft Open · verified Oct 22, 2026 At a glance
Mid-level ML Platform & Ops role at Jalasoft. Remote, Argentina · contract.
Pay not stated ML Platform & Ops salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build the course modules, lab exercises, reference implementation, evaluation harness and instructor materials
- Create a production-quality course artifact that can be handed to other instructors to teach
- Develop practical material around model fine-tuning, containerized inference and multi-tenant serving
- Cover quantization and caching approaches that demonstrate lower serving costs
What you bring
- A master’s in computer science or a related discipline
- At least five years shipping production software, including two or more years working on production AI or ML
- Hands-on experience fine-tuning classical ML or smaller foundation models and deploying containerized inference services
- Production experience with multi-tenant serving, including routing, queues or workload isolation
- Technical writing evidence and professional written English, plus reproducible development practices
Who this fits
This contractor role suits a mid-career engineer who can build the course materials personally and document technical work. It is remote from Argentina, and the finished materials will be taught by other instructors.
From the employer
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. You'll design module content, labs, a reference implementation, an evaluation harness, and an instructor guide.
Requirements
- Masters Degree in Computer Science or related
- 5+ years shipping production software, including 2+ in production AI/ML
- Able to personally build the course artifact to production standard
- Public evidence of technical writing (docs, technical blog, open-source project)
- Reproducibility discipline (pinned dependencies, containers, seeded runs)
- Willing to hand over developed material to the program (course will be taught by others)
- Track record fine-tuning classical ML / small foundation models
- Experience shipping containerized inference services to production
- Experience with multi-tenant serving in production (routing, queueing, isolation)
- Track record in quantization and caching, with demonstrable serving cost reduction
- Professional written English proficiency (test score, education in English, or work experience mainly in English).
- Proof of English proficiency (test score, education in English, or work experience mainly in English)
- Any extra proof of expertise, if available (publications, certifications, patents, training)
Tech Stack
Docker, Modal (CPU/T4/A10 and H100/A100), Hugging Face Hub, scikit-learn, PyTorch, vLLM, Prometheus, Grafana, Locust or k6
Benefits
- Remote work modality (home office).
- Joining a dynamic and growing organization with international reach.