Who are we looking for
We are looking for a motivated machine learning engineer to work closely with our lean and highly capable engineering team alongside software, and AI/ML engineers to develop a web application for our AI synthetic data generation platform.
The problems you will solve
Developing state-of-the-art AI generative models for structured data including GANs, autoencoders, language models (e.g. transformers, RNNs), etc.
Design success metrics that measures the privacy and quality of synthetic data generated
Translate success metrics into automated feedback loops to automatically improve the quality of synthetic data produced by the AI generative models
Integrate intelligent hyperparameter tuning into the models
Containerisation of data pipelines & AI models (Docker) with supporting orchestration tools (e.g. Kubernetes)
Hosting models to scalable cloud infrastructure (AWS / GCP)
Developing a clean and maintainable code using software engineering best-practices and modern platforms
Participating in full product development lifecycle from ideation to live production
Creating technical documentation
The impact you will have
Being part of a fast-growing and early stage start-up, you will be working together with the CTO and have the opportunity to take ownership of key parts of data & AI pipeline, make important technical decisions, and build a world-class product from the ground up.
About you
Proficient in:
Python
AI / ML frameworks (Pytorch, Keras, Tensorflow)
Data & ML libraries (Sklearn, numpy, pandas, plotly, matplotlib)
Experience in coding projects in any form (internships or experience in collaborating on multi-person coding projects in university / freelance / personal projects)
Ability to learn unfamiliar systems and forming an understanding of them through independent research, and working with a mentor and subject matter experts
Excitement about learning and building the future of data, privacy, and AI technology
We do not have rigid requirements for the subject you studied for your degree - an IT-related degree is great but so is any coding project / work experiences and your willingness to learn
Good to have
Experience hosting models to scalable cloud infrastructure (AWS / Azure / GCP)
Experience containerisation of the data pipelines & AI models in docker with supporting orchestration tools (e.g., kubernetes)
Experience in the ML lifecycle (experimentation, reproducibility, deployment, and a central model registry) and its supporting tools (e.g. MLflow)
As Andrew Ng said, "Don't worry about it if you don't understand". We know there are a lot of things we listed in what you will be doing and we do not expect you to have all of the skills needed at the start. Each of us at betterdata are learning something new every day. As long as you've demonstrated your interest with what you've done, read or contributed, please apply!
Benefits
Flexible time-off arrangements
Flexible work schedule - complete autonomy with no unnecessary meetings that take your time away from building
Flexible work arrangements - desk space at our office in One North Singapore or fully remote
How to apply
Does this role sound like a good fit to you?
Submit your application here
If the above does not work, you may email us your CV (pdf format) at jobs@betterdata.ai
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