Remote Python AI Logic Architect for LLM Training

Jazmin Par; United States; Remote; USD 28,000 - 69,000; Full time

Job summary

TELUS Digital is seeking a Python AI Logic Expert to guide Large Language Model training for data science, automation, and ML workflows. You will architect reasoning and ensure secure, enterprise-grade Python code across the AI community.

Responsibilities include designing advanced Python challenges, auditing model outputs for correctness and security, and validating ML libraries to maintain high fidelity results for SFT pipelines. Remote, international collaboration is essential.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Software Engineering, or Applied Mathematics.
• Advanced Python 3.x proficiency; decorators, generators, context managers, and standard library.
• Native language proficiency required for localization tasks.
• English proficiency: minimum B1 (Intermediate) for collaboration and documentation.
• Strong problem-solving and senior-specialist mindset toward automated outputs.

Responsibilities

• Design and refine Python challenges to teach chain-of-thought reasoning for data structures and algorithms.
• Review AI-generated Python scripts for PEP 8 compliance, security, and logic.
• Develop and optimize Python scripts for data cleaning, structuring, and augmentation for SFT.
• Evaluate libraries like Pandas, NumPy, PyTorch, and Scikit-learn for accuracy and performance.
• Create

Skills

Python

Decorators

Generators

Context managers

PEP 8

Education

Bachelor's degree in CS/DS/SE/Applied Mathematics

Tools

Python Standard Library

Pandas

NumPy

PyTorch

Scikit-learn

Job description

TELUS Digital is seeking a Python AI Logic Expert to guide Large Language Model training for data science, automation, and ML workflows. You will architect reasoning and ensure secure, enterprise-grade Python code across the AI community.

Responsibilities include designing advanced Python challenges, auditing model outputs for correctness and security, and validating ML libraries to maintain high fidelity results for SFT pipelines. Remote, international collaboration is essential.