Backend AI & Data Pipeline Engineer

Great internships are not only the ones that prepare you for the work you hope to do after completing your studies, but they are also the ones that help you realise what work you’re currently best suited for and where you might really fit in the working world. We give our interns work that help push their limits and capabilities whenever and wherever possible to prepare them for a future where new job opportunities may require you to become more skilled and efficient workers, especially with the rise of innovation in both business and IT.

SEEKA Technologies (Not Seeka Limited) is a project under its parent organization called Fresh Futures Australia which is an education consultant based in both Australia and Malaysia. We are developing and creating a platform that utilises A.I. to help match students and job seekers to the right opportunities relevant to them from Kindergarten up to the University along with vocational training centers and language schools and ofcourse to businesses and companies who need the right candidates. Our mission is to make it easier for anyone to find, filter and apply to educational institutions and companies in a more seamless manner.

We are currently looking to hire interns who want to work on the psychological aspects of human behavior, interaction and productivity with our application or website as well as explore how psychology plays a role in both the education industry and system. We are a company that recognizes the versatility of psychology majors and how applicable their skills are to a whole range of fields related to business, marketing, public relations, social media and more.

Bellow are the important details you will need to take note of:

• Only English is spoken on the job
• The minimum number of internship months we can accept is 2 months
• Both International Students and Locals are welcome to apply for this position

About the role

We are looking for a Backend AI & Data Pipeline Engineer to own the end-to-end data processing infrastructure that powers Yuzee's intelligent course and job matching platform. You will design and maintain scalable, event-driven pipelines that process tens of thousands of daily records, generate semantic embeddings, and feed a growing knowledge graph used for personalised career pathway recommendations.

What you'll do

• Design and maintain three distinct processing pipelines — scheduled job ingestion, event-driven course processing, and a periodic knowledge graph builder — each with independent trigger logic and cost controls
• Generate and manage semantic embeddings via Amazon Bedrock (Titan v2), index them in MongoDB Atlas Vector Search, and calibrate similarity thresholds to ensure match accuracy
• Build and maintain a knowledge graph linking jobs, courses, skills, and industries using FP-Growth association rules and archetype-to-SOC code mapping
• Build and improve a two-stage discovery and matching API on AWS Lambda — vector retrieval first, then deep eligibility scoring with LLM re-ranking
• Right-size Fargate Spot instances and design resumable processing loops that tolerate interruption, keeping infrastructure costs under control as data volume scales
• Maintain and improve daily job scrapers across multiple sources and build institution data scrapers with robust HTML cleaning pipelines

What we're looking for

• 1+ years of backend engineering experience focused on data pipelines, ML infrastructure, or search systems
• Hands-on experience with AWS serverless and container services — Lambda, ECS Fargate, EventBridge, and Step Functions
• Strong Python skills — Pandas, async processing, bulk database operations, and text cleaning
• Familiarity with vector databases and semantic similarity search; MongoDB Atlas Vector Search experience is a strong plus
• Cost-conscious infrastructure mindset — you think in per-record compute costs, free tiers, Spot resilience, and right-sizing
• Ability to document and communicate complex architecture clearly to both technical and non-technical stakeholders

Nice to have

• Experience with knowledge graphs or association rule mining (FP-Growth, Apriori)
• Experience using LLMs for re-ranking or eligibility assessment on top of vector retrieval results
• Background in edtech, jobtech, or recommendation/matching systems

Degree or existing proven experience 

Benefits 

• You can work from home for the whole internship period
• A reference letter can be requested upon completion of internship
• A bit of flexibility with working time aside from the usual 9am to 6pm (Ex. 8am to 5pm / 7:30am to 4:30pm)
• The possibility of retainment for part-time or Full-time work post-internship based on your performance, even if you are not based in Malaysia