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Machine Learning Engineer

Role overview

Qualifications

  • 2+ years of professional experience in Machine Learning Engineering, Applied ML, AI Engineering, or a related field.
  • Strong hands-on programming experience in Python.
  • Practical experience with ML frameworks such as PyTorch.
  • Experience working with Hugging Face Transformers and modern LLM architectures.

Responsibilities

  • Work with existing machine learning codebases to understand their architecture, functionality, dependencies, and implementation.
  • Develop, modify, debug, and improve ML implementations using Python and frameworks such as PyTorch.
  • Support model fine-tuning, inference, and evaluation to assess performance, accuracy, and output quality.
  • Document technical changes, findings, and evaluation outcomes where required.

Key facts

Hard skills

Other skills

  • Problem Solving
  • Analytical Thinking

About the company

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Masai

  • Vocational Training & Bootcamps
  • 201–500
On a mission to make tech careers accessible to everyone, no matter their financial or educational backgrounds.

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Job description

Posted by Masai | Opportunity with Neev Labs
About Neev Labs

Neev Labs unlocks the world's knowledge to advance frontier AI. The company sources, prepares, and licenses enterprise data, combining domain expertise with rigorous quality standards for AI model training and evaluation. Its mission is to make real-world knowledge a foundation for more capable AI.

About the Role

Neev Labs is looking for a skilled Machine Learning Engineer to contribute to projects involving modern machine learning systems, large language models (LLMs), and AI model evaluation. The ideal candidate should be comfortable working independently with existing ML codebases, understanding model architectures, implementing improvements, and evaluating model performance.

This opportunity is ideal for professionals who want to apply their practical ML engineering skills to advanced AI projects while working on a flexible, part-time basis.

Key Responsibilities

  • Work with existing machine learning codebases to understand their architecture, functionality, dependencies, and implementation.

  • Develop, modify, debug, and improve ML implementations using Python and frameworks such as PyTorch.

  • Work with Hugging Face Transformers and modern transformer-based model architectures.

  • Support model fine-tuning, inference, and evaluation to assess performance, accuracy, and output quality.

  • Apply prompt engineering and fine-tuning techniques to improve model behaviour and task-specific performance.

  • Investigate model-related issues, troubleshoot implementation challenges, and suggest improvements.

  • Review existing code independently and identify relevant components for implementing required changes.

  • Use Git/GitHub for version control, collaboration, code reviews, and maintaining development workflows.

  • Document technical changes, findings, and evaluation outcomes where required.

Required Qualifications

  • 2+ years of professional experience in Machine Learning Engineering, Applied ML, AI Engineering, or a related field.

  • Strong hands-on programming experience in Python.

  • Practical experience with ML frameworks such as PyTorch.

  • Experience working with Hugging Face Transformers and modern LLM architectures.

  • Strong understanding of transformer-based models, model fine-tuning, inference, and evaluation methodologies.

  • Familiarity with prompt engineering and techniques for adapting models to specific tasks.

  • Ability to independently read, understand, navigate, and modify existing ML codebases.

  • Experience with Git/GitHub and collaborative software development workflows.

  • Strong analytical thinking, debugging, and problem-solving skills.

Opportunity Highlights

  • Shared By: Masai

  • Time Commitment: 10–15 hours per week

  • Hourly Pay: $30–$80, based on experience and expertise

  • Work Arrangement: Flexible, remote opportunity

Why Consider This Opportunity?

  • Work on projects involving modern AI and machine learning technologies.

  • Apply your expertise to practical ML engineering and model evaluation challenges.

  • Enjoy a flexible, remote working arrangement alongside other professional commitments.

  • Contribute to initiatives supporting the development and evaluation of advanced AI systems.

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