Senior ML Engineer & MLOps Lead (Python/AWS)

RAPSYS TECHNOLOGIES PTE. LTD.

Singapore

On-site

SGD 180,000 - 240,000

Full time

14 days+

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Job summary

RAPSYS TECHNOLOGIES PTE. LTD.

in Singapore seeks a senior Data Scientist to lead the end-to-end ML/AI project lifecycle—from business problem framing and data exploration to feature engineering, model training, validation, deployment and ongoing monitoring. You will build and implement ML/AI or optimization solutions to boost performance, forecast demand, and optimize resources, collaborating with data and software engineers to deploy in cloud or air-gapped environments, and present actionable

Qualifications

  • At least 8 years relevant data science experience, including 2+ years in a lead or senior role.
  • Bachelors or Masters in CS/CE/Statistics/Data Analytics or related field.
  • Proficiency in Python and ML libraries; experience with MLOps tools.

Responsibilities

  • Lead end-to-end ML/AI project lifecycle from problem definition to deployment and monitoring.
  • Develop ML, AI or optimization models to address performance, forecasting, resource optimization, or customer outcomes.
  • Collaborate with data and software engineers to deploy ML/AI models in air-gapped and cloud production environments.
  • Drive experimentation and continuous learning using AI techniques such as time-series forecasting, anomaly detection, CV and NLP.
  • Present data-driven insights and recommendations in actionable business terms to business users.

Skills

Leadership
Communication
Problem-solving

Education

Bachelor's or Master's Degree in CS/CE/Statistics/Data Analytics/Applied Mathematics or relevant field

Tools

Python
Nifi
Airflow
SQL
pandas
numpy
scikit-learn
TensorFlow
PyTorch
Databricks
Snowflake
AWS SageMaker
Power BI
Qlik
Tableau

Job description

RAPSYS TECHNOLOGIES PTE. LTD.

in Singapore seeks a senior Data Scientist to lead the end-to-end ML/AI project lifecycle—from business problem framing and data exploration to feature engineering, model training, validation, deployment and ongoing monitoring. You will build and implement ML/AI or optimization solutions to boost performance, forecast demand, and optimize resources, collaborating with data and software engineers to deploy in cloud or air-gapped environments, and present actionable

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