Uma candidatura feita para esta oferta — um currículo e uma carta de apresentação personalizados que vão ao encontro do anúncio.
EFUNITY PTE. LTD. invites a Python-focused engineering intern to join the R&D team, handling a live data pipeline and a facial-recognition module deployed on customer sites.
You will maintain ingestion from AWS S3 through Redis Streams and MQTT into PostgreSQL, and own a computer-vision script using OpenCV. Expect on-site work about one day per week with the team.
About the role
This is a real engineering seat, not a shadowing placement. You will join the R&D team and take over live work from a departing intern — a running data pipeline and a facial-recognition module that is deployed on active customer sites. Most of your time is Python. You will maintain and extend an ingestion pipeline that moves data from AWS S3 through Redis Streams and MQTT into PostgreSQL, and you will own a computer-vision script that pulls frames from IP cameras over RTSP and runs them through a face-recognition pipeline. That script currently has a latency and detection problem to help solve. About one day a week you will be on site with engineers — HDB blocks, switch rooms, rooftops — commissioning and troubleshooting the systems your code runs on. You will report to the Senior Embedded Engineer and work alongside two software developers and the Engineering Director. You will present your own work at daily scrum from your first week.
Key responsibilities
Maintain and extend the S3 → Redis Stream → PostgreSQL ingestion pipeline: the publisher that stages files and emits MQTT messages, the subscriber that loads them into Postgres, and the acknowledger that reconciles stream entries against database rows.
Complete the migration from a Redis-list bridge to a webhook-based bridge into the Redis Stream.
Evaluate PostgreSQL NOTIFY/LISTEN against MQTT quality-of-service semantics and recommend which to standardise on.
Build in the error handling, retry and observability the pipeline needs to run unattended.
Own the Python facial-recognition script used on FSA installations.
Complete the move from ISAPI snapshot polling to direct RTSP capture with OpenCV, and resolve the current frame-latency and missed-detection problems.
Test and validate camera model changes — configuration backup and restore, one-for-one replacement, and verification that video analytics and face recognition still behave after a swap.
Measure what you change with before-and-after numbers on latency and detection rate.
Join site visits across live FSA projects to support installation, mock testing and commissioning, and fault rectification.
Troubleshoot edge hardware on site — controllers, panels, cameras, relays, power and network.
About you
Currently pursuing a degree in Computer Science, Software Engineering, Computer Engineering, Information Technology or a related discipline, with a 12-month IWSP or industrial attachment window.
Genuinely comfortable in Python — able to read, debug and extend someone else's code, not only write your own from scratch.
Some hands-on exposure to at least two of: PostgreSQL or other SQL databases, Redis, MQTT, Docker, Linux, AWS, OpenCV.
Able to work independently and say clearly, every morning, what worked and what did not.
Willing and able to attend customer sites, including switch rooms and rooftops, roughly one day a week.
Singapore Citizen or Permanent Resident, or holding a valid Student Pass with an approved IWSP or internship arrangement.