Implicant Pte. Ltd. is a Singapore deep-tech spin-off from NTU SPMS. We build machine learning models that are interpretable by design and run on encrypted data using fully homomorphic encryption (FHE). We are building a managed cloud platform for FHE-protected interpretable model training and inference, targeting financial services, defense, healthcare, and clinical analytics.
Job Description:
Build and ship features across the Implicant platform end-to-end, from database migration through API to frontend, with no handoffs.
Extend the training and inference platform (data ingestion, training jobs, Pareto frontier analysis, rule extraction, distillation pipelines).
Maintain and grow the customer-facing dashboard (inference page, model catalogue, billing).
Co-build the external API and Python SDK alongside the current full-stack lead.
Implement the FHE bootstrap key onboarding flow for clients running encrypted inference.
Wire Stripe billing and metering into the platform.
Own backend workflows for training jobs and asynchronous compute (FastAPI with Temporal-style orchestration).
Contribute to platform security and reliability (row-level security, authentication, audit logging).
Job Requirements:
Bachelor's degree in Computer Science, Software Engineering, or a related field.
4 years of relevant experience
Proven experience as full-stack engineer
Effective communication and interpersonal skills to collaborate with other engineers.
At least 3 years of full-stack experience shipping customer-facing software end-to-end.
Strong working knowledge of Python with FastAPI (or similar) and TypeScript with a modern frontend framework (Svelte preferred; React or Vue acceptable).
Production experience with PostgreSQL, including row-level security.
Good understanding of Machine Learning (architecture principles and ML librairies)
ML-literate: comfortable reading scikit-learn and PyTorch code and working with tabular machine learning workflows.
Comfortable in a small team with direct ownership and minimal process overhead.
Based in Singapore or willing to relocate.
We regret that only shortlisted candidates will be notified.
Hiring Institution: NTU
