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Intern, AI/ML [COO-GET-ENG]
Autodesk
Design and make software for architecture, engineering, construction, and entertainment industries.
Build AI-powered incident response assistant with Slack, KB, embeddings, LLMs.
10d ago
Entry-level
Internship
Singapore, Singapore
Office Full-Time
Company Size
11,600 Employees
Service Specialisms
Design
Engineering
Construction
Architecture
Consulting
Product Development
Technology Solutions
Software Development
Sector Specialisms
Building Design
Construction
Automotive
Building Product Manufacturing
3D Animation
Architecture
Engineering
Construction Professionals
Role
What you would be doing
slack integration
log analysis
knowledge base
llm integration
rag pipeline
aws deployment
Implement Slack integration to enable instant responses to production failures.
Work on log and monitoring data analysis to detect anomalies and assist with troubleshooting.
Build and maintain a central knowledge base with embeddings and vector search for fast retrieval.
Integrate with LLMs (via AWS Bedrock/Claude) for contextual reasoning and generating responses.
Enhance the retrieval-augmented generation (RAG) pipeline with filtering, similarity search, and grounding strategies.
Prototype automated tools like incident similarity search and AI-generated runbooks.
Develop pipelines to ingest, chunk, and embed content from wikis, GitHub repos, monitoring data, and Slack conversations.
Mentorship from experienced engineers in cloud platforms, and DevOps automation.
Collaborate with the engineering team to test and deploy solutions on AWS (ECS, S3, Lambda, OpenSearch).
What you bring
python
node.js
aws
machine learning
slack api
problem solving
Knowledge of logs, monitoring data, and incident response workflows is a strong plus.
Understanding of machine learning and NLP concepts (embeddings, vector search, RAG).
Exposure to AWS services (ECS, S3, Lambda, Bedrock, OpenSearch) is advantageous.
Problem-solving mindset with ability to debug, test, and iterate quickly.
Familiarity with Slack API integration and chatbot development.
Hands-on experience in building AI systems for real-time incident response.
Strong programming skills in Python and/or Node.js.
Learn how to integrate knowledge bases, embeddings, and LLMs for troubleshooting automation.
Benefits
Opportunity to work with production-scale observability data (logs, monitoring, Slack).
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