AIML Engineer

Crédit Agricole Group; Singapore; On-site; USD 60,000 - 100,000; Full time

Job summary

An established industry player is seeking a talented AI/ML Developer to join their innovative team. In this role, you will design and develop cutting-edge AI models, contribute to MLOps infrastructure, and collaborate with various stakeholders to address complex challenges. Your expertise in machine learning, deep learning, and generative AI will be pivotal in transforming data into actionable insights. This dynamic environment offers opportunities for continuous learning and growth, making it an exciting chance to impact the future of technology in an international banking context.

Qualifications

• 2 to 7 years of experience in AI/ML technology solutions development.
• Expertise in machine learning, deep learning, and generative AI.

Responsibilities

• Design and develop AI models, ensuring quality and scalability.
• Collaborate with business teams to translate needs into scientific questions.

Skills

Machine Learning

Deep Learning

Generative AI

MLOps

Python

Problem-Solving

Effective Communication

Education

Bachelor's in Computer Science

Bachelor's in Information Technology

Bachelor's in Programming & Systems Analysis

Bachelor's in Science (Computer Studies)

Tools

TensorFlow

PyTorch

Scikit-learn

GitLab CI/CD

Kubernetes

AWS Cloud

AWS Bedrock

AWS SageMaker

Job description

Job Responsibilities

· Responsible for the design, development, maintenance of applications and systems as well as IT production and management of the Bank's technical infrastructures.

· At the forefront of technological innovation, its teams provide technical and functional support for the development activities and projects of the various Corporate and Investment Banking professions in an international environment.

Design and development of AI/IA Generative models: Data preparation, feature engineering, training, evaluation, versioning, deployment and monitoring. Select the most appropriate models and techniques based on the available data and the objectives of the projects.
Establish MLOps / LLMOps infrastructure: Define and implement a robust MLOps architecture to ensure the full life cycle of AI and Generative AI models from design to production. Automate model development, deployment and monitoring processes.Ensure the quality, reliability and scalability of models in production.

Contribute to realisation of Rest API and development in Python, industrialisation of internal POCs and maintenance of embeddings. Ensure necessary documentation and support handover processes
Work closely with business teams and other project stakeholders to understand their needs and translate their issues into scientific questions. Communicate the results of the analyses and recommendations in a clear and concise manner.
Coordinate with Cloud Centre of Excellence and Infrastructure teams to ensure project needs are addressed.
Travel: Occasional (specify)

Qualifications and Profile

Candidates should have:

· Experience required 2 to 7 years minimum in development of AI/ML technology solutions

· expertise in machine learning, deep learning, generative AI and MLOps.

· Knowledge of data management practices to clean, preprocess and transform data sets for model training

· Mastery of AI algorithms and frameworks (e.g., Tensorflow, PyTorch, Scikit, etc.)

· Knowledge of GEN AI and LLM technologies on the public Cloud using RAG patterns

· Understanding the ethical principles to better generate embeddings for GenAI.

· Expertise in Python, .NET or Java, DevOps / MLOps / LLMOps (GitLab CI/CD, Kubernetes, AWS Cloud, AWS Bedrock, AWS Sagemaker)

Other Professional Skills and Mindset

· Excellent problem-solving and analytical skills.

· Effective communication skills and ability to work collaboratively in a team.

· Excellent Aptitude, Curious to learn and inquisitive.

· Autonomous, self motivated and excellent team player.

Education Requirements

At least a Bachelor’s degree in any of these faculties:

· Computer Science

· Information Technology

· Programming & Systems Analysis

· Science (Computer Studies)