ML Engineer

2 days ago

Melbourne, Victoria, Australia Mark My Words Full time $120,000 - $180,000 per year

About the Role

We're building an advanced AI-powered search and retrieval system using our own fine-tuned language models. We're looking for a ML engineer with strong backend engineering skills to help us build, optimise, and deploy this system at scale.

What You'll Do

  • Fine-tune and optimize our proprietary language models for question-answering and tool use
  • Build and maintain the backend infrastructure for our AI search system
  • Implement efficient vector search using PostgreSQL with pgvector
  • Design and optimise async request handling and caching strategies
  • Develop data processing pipelines for ingestion and retrieval
  • Deploy and monitor models in production with a focus on performance and cost

Required Skills

ML/AI Expertise:

  • Hands-on experience with TRL (Transformer Reinforcement Learning) library
  • Proven track record with SFT (Supervised Fine-Tuning) and DPO (Direct Preference Optimization)
  • Strong knowledge of Hugging Face Transformers ecosystem
  • Experience implementing tool/function calling for LLMs
  • Understanding of model deployment and inference optimization (vLLM, TGI, quantization)

Backend Engineering:

  • Expert-level Python with strong async/await programming skills
  • Production experience with PostgreSQL and pgvector for vector search
  • Caching implementation and optimization (Redis or similar)
  • Experience with data manipulation and ETL pipelines
  • API design with streaming responses

System Design:

  • Building scalable, production-grade ML systems
  • Performance optimization and monitoring
  • Cost-effective inference strategies

Nice to Have

  • Experience with RAG (Retrieval-Augmented Generation) architectures
  • Prompt Engineering
  • Knowledge of LoRA/QLoRA for efficient fine-tuning
  • Familiarity with embedding and reranking models
  • Web scraping and search API integration experience
  • Docker/Kubernetes deployment experience

What We're Looking For

A engineer who bridges ML and backend engineering - someone who can both fine-tune models and build robust production systems. You should be comfortable working with cutting-edge LLM techniques while maintaining production-quality code and infrastructure.

Tech Stack

Python, PostgreSQL (pgvector), Transformers/TRL, FastAPI, Redis, GPU infrastructure

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