Machine Learning Engineer

SCIENTEC CONSULTING PTE. LTD.; Singapore; Hybrid; SGD 125,000 - 150,000; Full time

Job summary

A consulting firm in Singapore is seeking a Machine Learning Engineer to design, build, and deploy scalable ML models. The ideal candidate has 2-3 years of experience in applied machine learning, strong proficiency in Python, and knowledge of ML frameworks like TensorFlow and PyTorch. This role includes a hybrid work arrangement, offering up to $10k in salary.

Qualifications

• 2-3 years of hands-on experience in applied machine learning or data science.
• Strong knowledge of ML frameworks.

Responsibilities

• Design, train, and evaluate machine learning models for diverse use cases.
• Collaborate with software engineers to integrate ML models into production systems.

Skills

Applied machine learning

Data science

Software engineering

Python

ML frameworks

Education

Bachelor’s degree in Computer Science or related fields

Tools

TensorFlow

PyTorch

scikit-learn

Job description

Working Hours

Monday – Thursday (8.30am – 6pm), Friday (8.30am – 5.30pm) (Hybrid working arrangement)

Working Location

Punggol

Salary Package

Up to $10k

Employment type

Contract

We are seeking a Machine Learning Engineer with strong expertise in applied machine learning, data science, and software engineering. The successful candidate will design, build, and deploy scalable ML models to power intelligent data-driven products and solutions. This role requires a combination of hands‑on technical proficiency, problem‑solving ability, and collaboration with cross‑functional teams to deliver impactful and production‑ready machine learning systems.

Responsibilities

• Design, train, and evaluate machine learning models for diverse use cases such as prediction, classification, and generation.
• Conduct experiments to assess model performance and identify opportunities for improvement.
• Tune hyperparameters, refine architectures, and propose new modeling strategies to enhance model accuracy, scalability, and robustness.
• Collaborate with software engineers and product teams to build ML-driven product features such as recommendation engines, anomaly detection, or data analytics components.
• Develop and optimize data preprocessing pipelines and implement effective feature engineering strategies.
• Diagnose and troubleshoot issues related to model training, deployment, or data quality.
• Work closely with engineers to resolve integration challenges and ensure reliable model performance in production environments.
• Document model architectures, parameters, and evaluation metrics for internal and user‑facing reference.
• Communicate complex ML concepts in a clear and accessible way to both technical and non‑technical audiences.
• Work closely with software engineers to integrate ML models into production systems using APIs or microservices.

Requirements

• Bachelor’s degree or higher in Computer Science, Data Science, Artificial Intelligence, Statistics, or related fields. At least 2–3 years of hands‑on experience in applied machine learning, model development, or data science.
• Proficiency in Python and strong knowledge of ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

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