AI/ML Engineering Intern - Full stack - On-Premises LLM Deployment & NVIDIA Technologies
About ExpertEase AI ExpertEase AI is a high-velocity startup backed by Microsoft, AWS, and NVIDIA, exploring sovereign AI solutions and on-premises infrastructure. We're researching and prototyping next-generation AI deployment models that give organizations control over their data and models.
You must be either Uni student or completing a Professional Year Program to apply.
The Learning Opportunity Gain hands-on experience with cutting-edge AI infrastructure technologies alongside our expert engineering team. You'll explore NVIDIA NeMo Framework, on-premises LLM deployment, and voice AI systems—building foundational skills that are shaping the future of enterprise AI. This is a structured learning experience where you'll develop practical expertise in emerging AI infrastructure technologies.
This is an Unpaid Educational Internship Opportunity.
What You'll Learn & Gain Experience With:
* NVIDIA NeMo Framework for LLM customization and deployment
* On-premises model hosting, optimization, and inference pipelines
* Voice AI systems using SIP protocols, WebRTC, and real-time audio streaming
* LLM evaluation frameworks and benchmarking methodologies
* GPU-accelerated computing and containerized AI deployments
* Prompt engineering and model fine-tuning techniques
* MLOps practices for local AI infrastructure
Technical Skills You'll Develop:
* LLM Frameworks: Hands-on with LangChain, LlamaIndex, NVIDIA NeMo
* Evaluation Tools: Experience with LLM evaluation frameworks, benchmarking, and quality metrics
* Python AI Stack: PyTorch, Transformers, FastAPI
* Voice AI Tech: Real-time audio processing, speech-to-text/text-to-speech integration
* Infrastructure: Docker, Linux systems, GPU computing basics
* Testing & QA: Building evaluation pipelines and testing methodologies
What We're Looking For:
* Strong Python programming foundation, REST APIs
* Experience independently setting up development environments and troubleshooting configuration issues
* Understanding of system architecture and how different components communicate
* Understanding of data flow between frontend, backend, and AI services
* Experience with system integration patterns and microservices concepts
* Genuine interest in LLMs and AI infrastructure
* Understanding of machine learning concepts
* Comfortable with Linux and command-line tools
* Self-directed learner who asks questions
* Ability to work independently in a fast-paced environment
Ideal Background:
* Previous exposure to Docker, containerization, or virtualization
* LLM's, LangChain,
RAG
* Understanding of websockets and real-time communication protocols
* Experience with database systems and state management
* Familiarity with cloud providers (Azure, AWS) and their AI services
* Knowledge of message queues and asynchronous processing
What Makes This Valuable for You:
* Direct mentorship from our experienced AI engineers including access to NVIDIA, Azure, AWS and Google Engineers.
* Exposure to enterprise-grade AI infrastructure
* Portfolio-worthy projects in emerging AI technologies
* References and potential pathway to future opportunities
* Real-world experience with NVIDIA's latest AI frameworks
Location: Adelaide office
Please apply with a cover letter explaining your suitability addressing the above job description.