Machine Learning Enginee

RESOURCES ID (PT Antam Resourcindo); United States; Remote; USD 83,000 - 152,000; Part time

Job summary

RESOURCES ID (PT Antam Resourcindo) is seeking a part-time remote Machine Learning Engineer to design, implement, and optimize ML models that support data-driven initiatives. You will preprocess datasets, build and evaluate models, and refine algorithms for pattern recognition and predictive analytics.

You will collaborate with cross-functional stakeholders, translate business needs into technical specs, document workflows, and present findings clearly.

Qualifications

• Strong CS foundations, algorithms, data structures, and software engineering principles.
• Experience building and evaluating ML models for classification, regression, or anomaly detection.
• Familiarity with statistics, probability, hypothesis testing and evaluation metrics.

Responsibilities

• Design, implement, and optimize ML models to support data-driven initiatives.
• Preprocess datasets, build and evaluate models, and refine algorithms for pattern recognition.
• Collaborate with stakeholders to translate business needs into technical specs and document workflows.
• Monitor model performance in production, iterate improvements, and ensure reproducibility and code quality.

Skills

Pattern recognition

Neural networks

Statistics

Problem solving

Communication

Data cleaning

Feature engineering

Education

Bachelor's degree in CS / Data Science / Engineering or equivalent

Tools

Python

TensorFlow

PyTorch

scikit-learn

Git

Job description

Role Description This part-time remote Machine Learning Engineer role focuses on designing, implementing, and optimizing machine learning models that support RESOURCES ID’s data-driven initiatives. Day-to-day activities include exploring and preprocessing datasets, building and evaluating models, and refining algorithms for pattern recognition and predictive analytics. The engineer will collaborate with cross-functional stakeholders to translate business needs into technical specifications, document workflows, and present findings in clear, actionable formats. Responsibilities also include monitoring model performance in production, iterating on model improvements, and maintaining code quality and reproducibility using modern development practices. The role offers flexibility while requiring reliable communication, ownership of deliverables, and adherence to best practices in data privacy and ethics.

Qualifications

• Candidates should possess strong foundations in Computer Science and Algorithms, including data structures, complexity analysis, and software engineering principles.
• Candidates should possess skills in Pattern Recognition and Neural Networks, with experience building and evaluating models for classification, regression, or anomaly detection.
• Candidates should possess knowledge of Statistics, including probability, hypothesis testing, and model evaluation metrics.
• Candidates should possess proficiency in programming languages commonly used in machine learning (such as Python) and frameworks (such as TensorFlow, PyTorch, or scikit-learn).
• Candidates should possess the ability to work with real-world datasets, including data cleaning, feature engineering, and handling missing or noisy data.
• Candidates should possess strong problem-solving, analytical, and communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Relevant experience with cloud platforms, MLOps practices, version control (e.g., Git), and deployment of models to production environments is beneficial.
• A bachelor’s degree or higher in Computer Science, Data Science, Engineering, Mathematics, or a related field, or equivalent practical experience, is preferred.