Remote AI/ML Engineer - Build Cutting-Edge Models

Placements24; Queenstown; Remote; NZD 120,000 - 180,000; Full time

Benefits offered by this job

Health insurance

Performance bonuses

Remote work

Conference opportunities

Professional development

Job summary

Placements24 is seeking an exceptional AI/ML Engineer to join a fully remote team. You will design, build, and deploy advanced ML models, work with large datasets and state‑of‑the‑art methods, and collaborate with data scientists to produce production‑ready AI solutions.

The role emphasizes deep learning architectures, scalable pipelines, and rigorous evaluation, with strong emphasis on remote collaboration and global impact.

Qualifications

• Masters or PhD in CS/AI or related quantitative field.
• 3+ years hands-on experience in developing and deploying ML models.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn).
• Strong ML algorithms knowledge; NLP or CV is a plus.
• Experience with cloud platforms and big data processing.

Responsibilities

• Develop, train, and deploy ML models for various applications.
• Design AI algorithms and deep learning architectures.
• Process and analyze large datasets to extract insights.
• Build ML pipelines for data prep, training, evaluation.
• Collaborate with data scientists and engineers to productionize models.
• Optimize model performance for accuracy and scalability.
• Stay updated with AI research and advancements.
• Develop evaluation metrics and validation strategies.
• Contribute to AI system design and architecture.
• Document research methods and results clearly.

Skills

Python

TensorFlow

PyTorch

scikit-learn

Deep learning

Education

MS/PhD in CS/AI

Tools

AWS

Azure

GCP

Docker

Job description

Placements24 is seeking an exceptional AI/ML Engineer to join a fully remote team. You will design, build, and deploy advanced ML models, work with large datasets and state‑of‑the‑art methods, and collaborate with data scientists to produce production‑ready AI solutions.

The role emphasizes deep learning architectures, scalable pipelines, and rigorous evaluation, with strong emphasis on remote collaboration and global impact.