Act as an advisor to our founder, CTO and stakeholders to define our AI strategy.
Create a roadmap for AI research, development, and model deployment.
Partner with our AI team in designing, implementing, and optimizing machine learning models (especially large language models).
Utilize both external and proprietary machine learning tools and infrastructure to build adaptable, high-performance machine learning systems that facilitate rapid model development, efficient real-time deployment, and straightforward maintenance of model quality.
Closely collaborate with our engineering teams to ensure smooth end-to-end delivery of AI solutions.
Work closely with our infrastructure engineering team to build and leverage machine learning infrastructure to ensure that machine learning models run smoothly, scale effectively and deliver valuable insights.
Collaborate with our data team to understand data requirements. Clean, preprocess, and transform large scale structured and unstructured data for model training.
Rapidly prototype AI solutions, iterate, and learn from failures.
JOB REQUIREMENT
A Bachelor or Master in a quantitative field (Computer Science, Engineering, etc).
Minimum 7+ years of experience in AI, Machine Learning, Data Science roles.
Proven track record in delivering end-to-end ML projects: identifying impactful use cases, effort estimation, EDA, solution & model development, performance evaluation, deployment, and models monitoring.
Strong technical hands-on experience in Python.
Strong knowledge of Machine Learning fundamental i.e. knowledge of models variant and use cases, end-to-end ML lifecycle process, model development, model selection, hyperparameter optimisation, feature engineering, evaluation, etc.
Strong hands-on experience in Machine Learning algorithms & libraries like Tensorflow, Pytorch, Keras, Scikit, Pandas.
Experience in GenAI/LLM.
Hands-on experience in three or more of the following AI topics: NLP, recommendation systems, predictive analytics, computer vision, search.
Good hands-on experience in git, building CI/CD pipelines.
Experience on how to operate docker images in microservice architecture.
Experience in cloud platform GCP or AWS.
Experience in MLOps platform e.g. MLflow, or Kubeflow.
Hands-on experience in SQL.
Have a growth mindset, self-driven, high motivation & curiosity to learn.
Experience delivering and driving action based on data-driven insights.
BENEFIT
Multiple products and projects for SEA market in the healthcare domain
Work with our regional tech team from Singapore and Vietnam
Hybrid work model, flexible and flat hierarchy working environment
16 days of annual leave and 3 days of sick leave, +1 after each full-year service
Competitive salary range and 13th month salary
Insurance in full gross salary, Premium Healthcare Insurance