Responsibilities:
- Develop and deploy machine learning models: Design, build, and optimize machine learning models and algorithms to solve specific business problems. Collaborate with cross-functional teams to gather requirements, define objectives, and deploy models into production environments.
- Model training and evaluation: Train and fine-tune machine learning models using appropriate algorithms and techniques. Evaluate model performance and identify areas for improvement, employing techniques such as cross-validation, hyperparameter optimization, and ensemble methods.
- Model deployment and integration: Collaborate with software engineers and DevOps teams to deploy machine learning models into production environments. Implement APIs and integrate models with existing systems and applications to enable real-time decision-making.
- Performance monitoring and maintenance: Monitor model performance and address any issues or anomalies that arise. Continuously improve models by refining algorithms, optimizing code, and incorporating feedback from users and stakeholders.
- Data analysis and insights: Perform exploratory data analysis, generate insights, and present findings to stakeholders. Use statistical methods and visualization techniques to communicate complex concepts and patterns effectively.
Requirements:
- Education: Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field. An equivalent combination of education and experience will also be considered.
- Solid understanding of machine learning algorithms, techniques, and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience with working on Large Language Models and Generative AI technology is a plus.
- Strong programming skills in languages such as Python.
- Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn etc.
- Solid understanding of Statistical Analysis, Probability Theory, and Hypothesis Testing.
- Familiarity with machine learning tools on cloud platforms (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is a plus.
(EA Reg No: 20C0312)
Please email a copy of your detailed resume to [email protected] for immediate processing.
Only shortlisted candidates will be notified.
