Key responsibilities:
Design, develop, and deploy AI/ML models and solutions, including LLMs and GenAI.
Perform feature engineering and selection to optimize model performance.
Select and implement appropriate AI/ML algorithms, including supervised, unsupervised, and reinforcement learning models.
Deploy models to production environments, ensuring robustness and scalability.
Monitor model performance and define strategies for identifying drift; retrain or refine models as needed.
Collaborate with cross-functional teams to integrate AI/ML models with business applications and systems.
Train, evaluate, and optimize models using machine learning and statistical techniques.
Conduct extensive data exploration, analysis, and preprocessing to ensure data quality for AI/ML applications.
Develop and apply data science methodologies to extract insights from large-scale structured and unstructured datasets.
Utilise predictive analytics, time series forecasting, and statistical models to drive business decision-making.
Stay updated on the latest advancements in AI/ML and data science technologies.
Develop and maintain comprehensive documentation for AI/ML pipelines, data workflows, and analytical processes
Your Profile
Essential skills/knowledge/experience:
Good experience in AI/ML development and data science.
Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems.
Experience with machine learning frameworks (eg, TensorFlow, PyTorch) and data science libraries (eg, NumPy, pandas, scikit-learn).
Proficiency in Python, R, or other relevant programming languages.
Proficiency in working with large datasets, data wrangling, and data preprocessing.
Experience in data science, statistical modelling, and data analytics techniques.
Experience with data analysis and visualization tools (eg, Matplotlib, Seaborn, Tableau).
Ability to work independently and lead projects from inception to deployment.
Experience with big data technologies (eg, Hadoop, Spark) and cloud platforms (eg, AWS, GCP, Azure) is desirable.