Academic Content Developer (AI Optimization & Foundations)

Jalasoft; Argentina; A distancia; ARS 1.200.000 - 2.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work

International reach

Descripción de la vacante

Jala University seeks a seasoned AI/ML software engineer to bridge academia and industry by delivering practical education and hands-on production-grade tooling. You will design and implement optimizers from first principles, instrument training loops, and contribute to course artifacts.

Applicants should have 5+ years shipping production software, strong English writing skills, and experience with Python, PyTorch, Docker, and cloud platforms. Remote work is offered with international reach.

Formación

• Masters degree in CS or related field.
• At least 5+ years shipping production software, including 2+ years in production AI/ML.
• Able to implement optimizers from first principles and instrument gradient flow.
• Proficient in probability and information theory concepts.
• Ability to build course artifacts to production standard with instrumented optimizers.

Conocimientos

Production AI/ML

Python

PyTorch

Docker

Cloud platforms

NumPy

scikit-learn

Jupyter

Weights & Biases

English writing

Educación

Master's Degree in Computer Science or related

Herramientas

Docker

Jupyter

AWS

GCP

Azure

Descripción del empleo

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

• Masters Degree in Computer Science or related
• 5+ years shipping production software, including 2+ years in production AI/ML
• Able to implement optimizers from first principles (not by calling a framework's built-in optimizer) and instrument gradient flow, learning-rate schedules, and regularization diagnostics
• Working fluency in probability and information theory (likelihood, entropy, KL divergence)
• Able to personally build a course artifact to production standard, including an instrumented optimizer and analytical brief
• Hands-on with Python, NumPy, scikit-learn, PyTorch (basics through autograd/custom optimizer loops), Jupyter, Docker, one cloud VM (AWS/GCP/Azure), Weights & Biases, Modal (CPU + T4/A10), matplotlib
• 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

Benefits

• Remote work modality(home office).
• Joining adynamic and growing organizationwith international reach.