This role offers the opportunity to work on cutting-edge ML technologies and contribute to transformative business solutions in a dynamic and collaborative MNC environment.

JOB REQUIREMENTS:

• Min. Bachelor’s Degree in Computer Science, Data Science, Machine Learning, or a related field.
• At least 4 years of hands-on experience in designing, developing, and deploying ML models for real-world applications.
• Familiarity with Large Language Models and Generative AI technologies is a plus.
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Strong understanding of statistical analysis, probability theory, and hypothesis testing.
• Experience with cloud-based ML tools (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is advantageous.
• Excellent communication skills to articulate technical concepts to diverse stakeholders.
  Your recruiter for this job: WhatsApp Celine @ 6421 4966 for a quicker response.
  Connect with me on LinkedIn: www.linkedin.com/in/your-recruiter-celine-chan
  Celine Chan | R21103433
  Talentsis Pte Ltd | EA No: 20C0312

• Design, develop, and optimize machine learning (ML) models and algorithms to address business challenges.
• Collaborate with cross-functional teams to gather requirements, define objectives, and deploy models effectively.
• Train and fine-tune ML models using appropriate algorithms, techniques, and tools.
• Conduct evaluations to assess model performance, applying methods such as cross-validation, hyperparameter tuning, and ensemble learning.
• Work closely with software engineers and DevOps teams to deploy models in production environments.
• Implement APIs and integrate models into existing systems to enable real-time decision-making.
• Monitor deployed models to ensure optimal performance, address anomalies, and resolve issues.
• Continuously refine models and algorithms based on user feedback and performance metrics.
• Perform exploratory data analysis to uncover trends and insights.
• Use statistical methods and visualization techniques to communicate findings to stakeholders.
• Stay updated on advancements in ML and artificial intelligence (AI).
• Evaluate and recommend new tools, libraries, and methodologies to enhance workflows.