Remote ML Researcher: Innovative Model Developer

Quik Hire Staffing; Indonesia; Remote; IDR 1,592,638,000 - 2,300,478,000; Full time

Job summary

Quik Hire Staffing is seeking a Machine Learning Researcher (Remote) to support ongoing research initiatives in AI. You will develop and refine models to improve performance across applications and collaborate with cross-functional teams to validate and scale findings.

The role offers flexible contract duration aligned with project milestones and requires strong Python + ML framework skills to work autonomously in a remote setting.

Qualifications

• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Experience with deep learning architectures and optimization techniques.
• Strong background in statistical analysis and mathematical modeling.
• Knowledge of data preprocessing, feature engineering, and evaluation metrics.
• Ability to work independently in a remote environment with minimal supervision.

Responsibilities

• Design and implement novel machine learning models to address specific research challenges.
• Conduct experiments to evaluate model performance and iterate based on results.
• Collaborate with engineers and researchers to integrate models into production systems.
• Document methodologies, results, and insights for internal and external stakeholders.
• Stay current with advancements in machine learning research and apply relevant techniques.

Skills

Python

Deep Learning

Statistics

Model Optimization

Data Preprocessing

Feature Engineering

Evaluation Metrics

Independent Remote Work

Tools

PyTorch

TensorFlow

Job description

Quik Hire Staffing is seeking a Machine Learning Researcher (Remote) to support ongoing research initiatives in AI. You will develop and refine models to improve performance across applications and collaborate with cross-functional teams to validate and scale findings.

The role offers flexible contract duration aligned with project milestones and requires strong Python + ML framework skills to work autonomously in a remote setting.