The role involves designing, developing, and implementing advanced generative models using cutting-edge AI technologies to achieve business objectives.
AI/ML consultant partners with business stakeholders in leveraging artificial intelligence and machine learning technologies to identify areas where AI/ML can bring improvements, such as automating processes, improving customer experiences, or gaining insights from data.
WHAT YOU WILL DO
- Design, develop, and implement advanced generative models using cutting-edge AI technologies, and maintain machine learning and deep learning models.
- Research and integrate mature AI solutions from the market (e.g., OpenAI, Google AI) to enhance the app's intelligence, improving service efficiency and user experience.
- Select and implement appropriate AI APIs/models based on business requirements, optimizing applications in areas such as NLP, computer vision, and personalized recommendations.
- Design, develop, and implement AI models and algorithms for NLP and Computer Vision applications.
- Collaborate with data scientists and engineers to design and implement machine learning pipelines using MLOps practices for Data Preparation, Model Training/Re-Training, Deployment, Inference and Monitoring.
- Develop and deploy scalable REST APIs to expose ML models to various business applications for online inference.
- Develop and implement data pipelines for curation of structured/unstructured and semi-structured data for Feature Engineering, Model Training and Batch/Online Inference.
- Conduct research and development activities to improve the performance and efficiency of generative models.
WHAT YOU SHOULD HAVE
- A bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, or related fields.
- 3+ years of experience in a Machine Learning / Data Science and 1+ years of AI application development experience for specific industries such as financial institution, healthcare, finance or retail.
- Publications or contributions to the AI community through research papers, open-source projects, or conferences.
- Utilise frameworks like Langchain, Llamaindex, and Crew AI to create intelligent and autonomous agents.
- Strong knowledge of machine learning, deep learning, and generative models, with experience in training and fine-tuning GenAI models.
- Proven experience in machine learning operations (MLOps) and familiarity with mainstream AI services (e.g., OpenAI, Google AI) and hands-on experience with API integration.
- Strong proficiency in Python, with experience using AI frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers.
- Practical experience in at least one area, such as NLP, computer vision, speech recognition, or recommendation algorithms.
- Experience in leveraging and fine-tuning large language models (LLMs) and Small Language Models to optimize AI applications for specific business needs.
- Familiarity with natural language processing techniques (tokenization, NER, sentiment analysis).
- Experience with computer vision tasks (image classification, object detection, segmentation).
- Ability to work with large datasets and knowledge of data preprocessing techniques (handling missing data, data augmentation, normalization).
- Experience with cloud platforms and services (AWS, Google Cloud, Azure) for deploying AI solutions.
- Excellent communication skills and the ability to collaborate effectively with cross-functional teams.