AI Engineer – PyTorch & MLOps

Twine; New Zealand; On-site; NZD 120,000 - 180,000; Full time

Job summary

Twine is hiring for a senior ML/AI engineer to design, train, and deploy deep learning models in production. You will build scalable data pipelines, integrate models into cloud services, and monitor production performance in collaboration with cross-functional teams.

The role emphasizes MLOps, CI/CD, and reliability in mission-critical applications, with a strong focus on Python and one of C++/Java, plus experience with PyTorch, TensorFlow, or Scikit-learn.

Qualifications

• 3+ years of experience building and deploying ML models in production.
• Proficiency in Python and at least one of C++ or Java.
• Hands-on experience with PyTorch, TensorFlow, or Scikit-learn.

Responsibilities

• Design, train, deploy, and optimize deep learning models for production environments (PyTorch focus).
• Build scalable data processing pipelines for model training and inference.
• Integrate ML models into cloud services and APIs (AWS/GCP).
• Monitor model performance and troubleshoot production issues.

Skills

Python

C++/Java

Tools

PyTorch

TensorFlow

Scikit-learn

Docker

Kubernetes

AWS

GCP

SQL

Job description

Join a dynamic team focused on scaling advanced AI solutions for production environments. This role centers on building, training, deploying, and optimizing deep learning models, as well as developing robust data processing pipelines. You will collaborate closely with software, product, and data teams to integrate models into cloud-based services, ensuring seamless deployment and operational excellence. The position also involves monitoring model performance, troubleshooting issues, and driving improvements in speed and reliability for mission-critical applications.

Deliverables

• Design, develop, and deploy deep learning models using PyTorch and related frameworks
• Build and maintain scalable data processing pipelines for model training and inference
• Integrate machine learning models into cloud services (AWS or GCP) and APIs
• Monitor, evaluate, and optimize model performance in production environments
• Collaborate with cross-functional teams to deliver end-to-end AI solutions
• Implement MLOps best practices for continuous integration and deployment
• Troubleshoot and resolve issues related to model reliability and scalability

Requirements

• Minimum 3 years of experience building and deploying machine learning models in production
• Proficiency in Python and at least one of C++ or Java
• Hands-on experience with PyTorch, TensorFlow, or Scikit-learn
• Strong background in Docker, Kubernetes, and cloud platforms (AWS or GCP)
• Experience designing and maintaining data pipelines and APIs
• Solid understanding of MLOps, CI/CD, and model monitoring
• Advanced SQL skills for data manipulation and analysis
• Excellent English communication skills for collaboration with international teams
• Ability to work independently and deliver results in a fast-paced environment

About Twine

Twine is a leading freelance marketplace connecting top freelancers, consultants, and contractors with companies needing creative and tech expertise. Trusted by Fortune 500 companies and innovative startups alike, Twine enables companies to scale their teams globally.

Our Mission

Twine's mission is to empower creators and businesses to thrive in an AI-driven, freelance-first world.