AI & Machine Learning, Consultant

AIA SINGAPORE PRIVATE LIMITED; Singapore; On-site; SGD 100,000 - 150,000; Full time

Job summary

A leading company in Singapore is seeking an AI/ML consultant to design and develop advanced generative models using cutting-edge AI technologies. The role involves leveraging AI for business improvements, collaborating with data scientists, and implementing machine learning pipelines. The ideal candidate should have substantial experience in AI application development and be proficient in various AI frameworks and tools for machine learning.

Qualifications

• 7+ years of experience in Machine Learning and 3+ years in AI application development.
• Proficient in Python and AI frameworks.
• Strong knowledge of machine learning, deep learning, and generative models.

Responsibilities

• Design, develop, and implement advanced generative AI models.
• Collaborate with stakeholders to enhance AI solutions.
• Integrate AI APIs based on business needs.

Skills

Machine Learning

Deep Learning

Generative Models

Natural Language Processing

Computer Vision

Data Preprocessing Techniques

Cloud Platforms

Python

Education

Bachelor’s or Master’s degree in Computer Science or related fields

Tools

TensorFlow

PyTorch

Hugging Face Transformers

Langchain

Llamaindex

Crew AI

Job description

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.
• 7+ years of experience in a Machine Learning / Data Science and 3+ 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.