ML Engineer: Scale Research Models to Production (Remote)

Meta; Australia; Remote; AUD 120,000 - 160,000; Full time

Benefits offered by this job

Remote working

Collaborative environment

Ownership and growth opportunities

Job summary

Metacognition is seeking a Machine Learning Engineer to bridge research and production. You will transform experimental code into scalable systems, collaborating with researchers and engineers to deploy models on cloud infrastructure and optimize performance across compute environments.

The role values curiosity, rapid iteration, and a track record of shipping research or products in a team setting within an AI-focused startup. Remote-friendly environment and meaningful ownership are offered.

Qualifications

• Strong Python skills.
• Hands-on experience training and deploying deep learning models on cloud infrastructure.
• Familiarity with PyTorch or JAX.
• Genuine intellectual curiosity, collaborative mindset, and comfort working in a fast-paced research environment.
• Experience with large-scale model training (LLMs, vision-language models, or similar).
• Familiarity with simulation environments, synthetic data generation, or evaluation pipelines.
• Prior experience in a research lab, deep tech company, or AI-focused startup.
• Track record of shipping research or products in a collaborative team setting.

Responsibilities

• Implement, optimise, and scale machine learning models and training pipelines.
• Build robust data, simulation, and evaluation infrastructure.
• Bridge research and production - taking experimental code to reliable, efficient systems.
• Profile and optimise model performance across compute environments.
• Develop and maintain early-stage demonstrators of research ideas.

Skills

Python

DL model training

Cloud deployment

PyTorch / JAX

Large-scale training

Experiment to production

Research collaboration

Shipping research/products

Tools

PyTorch/JAX

Cloud infrastructure

Job description

Metacognition is seeking a Machine Learning Engineer to bridge research and production. You will transform experimental code into scalable systems, collaborating with researchers and engineers to deploy models on cloud infrastructure and optimize performance across compute environments.

The role values curiosity, rapid iteration, and a track record of shipping research or products in a team setting within an AI-focused startup. Remote-friendly environment and meaningful ownership are offered.