Remote MLOps Engineer: Build Scalable ML & LLM Infra

01.tech; Victoria; Remote; AUD 140,000 - 190,000; Full time

Benefits offered by this job

Annual benefits allowance

Relocation assistance after probation

Corporate digital library

Weekly online sessions with a mental-w

Job summary

01.tech is seeking a skilled MLOps Engineer to design, build, and maintain a scalable ML platform. You will automate the full model lifecycle—from training and validation to deployment, monitoring, and retraining—and develop AutoML infrastructure for experiments, tuning, and production promotions.

You will implement MLflow, build a feature store, and orchestrate pipelines with Airflow for batch and real-time scoring.

Qualifications

• Hands-on experience building or operating MLOps infrastructure or ML platforms.
• Strong Python and Linux skills, including infrastructure automation and development of supporting services.
• Experience with Docker and a solid understanding of Kubernetes and container orchestration.
• Experience building CI/CD pipelines and managing infrastructure using Terraform, Ansible, or similar tools.
• Solid understanding of the full ML model lifecycle, including training, validation, registration, deployment, monitoring, and retraining.
• Experience with MLflow, Airflow, Feature Stores, or comparable technologies.
• Experience implementing monitoring, logging, alerting, and troubleshooting for production systems.
• Understanding of batch scoring and real-time inference architectures.
• Experience integrating services with message brokers and analytical data stores.
• Experience building AutoML platforms and automating experiments using Optuna or Ray Tune.
• Hands-on experience deploying and operating LLMs or building LLMOps infrastructure.

Responsibilities

• Design, build, and maintain an ML platform that automates the entire model lifecycle, from training and validation to deployment, monitoring, and retraining
• Develop AutoML infrastructure to automate experiments, hyperparameter tuning, model evaluation, and promotion from staging to production
• Implement and maintain MLflow or similar tools for experiment tracking, model versioning, and reproducibility
• Design and maintain a Feature Store with online and offline storage, ensuring point-in-time correctness and feature consistency between training and inference
• Automate training, retraining, and scoring pipelines using Airflow and other orchestration tools, supporting both batch scoring and real-time inference
• Build CI/CD pipelines for ML, including automated data and model testing, quality checks, safe deployments, and rollback mechanisms
• Implement production monitoring for ML systems, covering availability, latency, throughput, resource utilization, data drift, concept drift, and model performance
• Containerize, deploy, and scale ML services using Docker and Kubernetes, ensuring reliability and fault tolerance
• Develop Infrastructure as Code (IaC) practices and manage environments, configurations, secrets, and access using Terraform, Ansible, Vault, and similar tools
• Work closely with Data Engineering to integrate the ML platform with ClickHouse, Kafka, PostgreSQL, Redis, and other data infrastructure components
• Establish MLOps standards, reusable pipeline templates, and tooling that streamline model development, testing, and operations for Data Science and ML Engineering teams

Skills

MLOps

Python

Linux

Docker

Kubernetes

CI/CD

Terraform

Ansible

Airflow

MLflow

vLLM

Ollama

LiteLLM

Data streaming

Tools

Docker

Kubernetes

Terraform

Ansible

Airflow

MLflow

ClickHouse

Kafka

Job description

01.tech is seeking a skilled MLOps Engineer to design, build, and maintain a scalable ML platform. You will automate the full model lifecycle—from training and validation to deployment, monitoring, and retraining—and develop AutoML infrastructure for experiments, tuning, and production promotions.

You will implement MLflow, build a feature store, and orchestrate pipelines with Airflow for batch and real-time scoring.