MLOps Engineer - Hybrid AI, LLMs & CI/CD Deployments

Employers Mutual Management Pty Ltd; Sydney; Hybrid; AUD 120,000 - 170,000; Full time

Benefits offered by this job

Hybrid work options

Fitness Passport discounts

RewardsHub retailer discounts

Wellbeing program

Learning & development opportunities

Job summary

EML is seeking a skilled MLOps Engineer to design, build and maintain scalable Python applications, RESTful APIs and AI workflows in production. You will deploy and optimise LLM inference workloads using vLLM and Ray, and develop containerised services with Docker and Kubernetes.

You will apply prompt engineering techniques, collaborate with technology, AI and business stakeholders, and help deliver secure, production-ready AI solutions with a specialist organisation focused on personal injury.”

Qualifications

• 2+ years of experience as a MLOps engineer or Software Engineer.
• Strong Python development skills and production-ready RESTful APIs.
• CI/CD pipelines experience with GitHub Actions.
• Containerisation with Docker and Kubernetes in production.
• Experience deploying and serving LLMs (vLLM, Ray).
• Knowledge of prompt engineering and LLM evaluation techniques.

Responsibilities

• Design, develop and maintain scalable Python applications and AI solutions.
• Build and optimise CI/CD pipelines (GitHub Actions).
• Deploy and optimise LLM inference workloads in production.
• Develop and maintain containerised apps with Docker and Kubernetes.
• Apply prompt engineering and inference optimisation techniques.
• Collaborate with technology, AI and business stakeholders to deliver secure solutions.

Skills

Python

REST APIs

CI/CD

GitHub Actions

Docker

Kubernetes

Linux Bash

LLM inference

Prompt engineering

Collaboration

Tools

FastAPI

vLLM

Ray

Job description

EML is seeking a skilled MLOps Engineer to design, build and maintain scalable Python applications, RESTful APIs and AI workflows in production. You will deploy and optimise LLM inference workloads using vLLM and Ray, and develop containerised services with Docker and Kubernetes.

You will apply prompt engineering techniques, collaborate with technology, AI and business stakeholders, and help deliver secure, production-ready AI solutions with a specialist organisation focused on personal injury.”