Junior ML Engineer - Autonomy & Real-World Driving Data

Wingfin Singapore

Singapore

On-site

SGD 60,000 - 90,000

Full time

3 days ago
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Job summary

Wingfin Singapore is seeking an entry-level Machine Learning Engineer to join our team in Singapore. This role focuses on preparing and processing data for ML training, running experiments and understanding model behavior on real-world driving data.

You will work across perception, planning and control pipelines, with opportunities to contribute to model development and evaluation infrastructure as we scale. A strong academic foundation in Physics, Math, or Engineering is valued.

Qualifications

  • Bachelor's degree or higher in Physics, Mathematics or Engineering with strong academic record.
  • Some practical experience with machine learning from university, research, projects or competitions is acceptable.
  • Proficiency with Python and use of modern AI tools is preferred.

Responsibilities

  • Prepare and process large autonomous-driving datasets for ML training.
  • Build pipelines to extract, clean, label and organize sensor data.
  • Inspect datasets for errors and data-quality issues.
  • Develop tools to identify useful driving scenarios for training examples.
  • Run ML experiments and analyze results.
  • Collaborate with engineers on perception, planning and control models.
  • Help improve training and evaluation infrastructure as datasets grow.

Skills

Python programming
Numerical analysis
Hands-on experimentation
Data processing

Education

Bachelor's degree in Physics, Mathematics or Engineering

Tools

PyTorch
TensorFlow
Linux
Git

Job description

Wingfin Singapore is seeking an entry-level Machine Learning Engineer to join our team in Singapore. This role focuses on preparing and processing data for ML training, running experiments and understanding model behavior on real-world driving data.

You will work across perception, planning and control pipelines, with opportunities to contribute to model development and evaluation infrastructure as we scale. A strong academic foundation in Physics, Math, or Engineering is valued.

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