Machine Learning Engineer

Jobgether; India; A distancia; INR 3.921.000 - 10.456.000; A tiempo parcial

Ventajas ofrecidas por este puesto de trabajo

Competitive hourly pay (USD 30–80)

Fully remote in India

Flexible 10–15 hours per week

Exposure to cutting-edge AI projects

Professional development opportunities

Descripción de la vacante

Jobgether on behalf of a partner company in India seeks a Machine Learning Engineer for a flexible remote, part-time role. You will work with Python, PyTorch, and Hugging Face Transformers on LLMs and transformer architectures, focusing on fine-tuning, inference, and evaluation.

You will review existing ML code, implement improvements, and collaborate via Git/GitHub while contributing to advanced AI projects. Independent, responsible work is expected.

Formación

• At least 2 years of professional ML engineering experience.
• Strong Python programming skills.
• Hands-on experience with PyTorch.
• Experience with Hugging Face Transformers and LLMs.
• Knowledge of transformer architectures.
• Experience with model fine-tuning and inference.
• Familiarity with evaluation methodologies.
• Experience with prompt engineering.
• Ability to read and modify existing ML codebases.
• Strong Git/GitHub collaboration.

Responsabilidades

• Understand existing ML systems: review and navigate codebases to understand architecture and dependencies.
• Develop and improve ML implementations using Python and PyTorch.
• Work with transformer-based models and LLMs via Hugging Face Transformers.
• Support model fine-tuning to adapt models to tasks and improve outputs.
• Perform inference and evaluation, assess accuracy and performance.
• Apply prompt engineering techniques to improve responses.
• Troubleshoot issues, identify performance gaps and propose improvements.
• Manage development workflows with Git and GitHub, including reviews.
• Document findings, decisions, and results for continuity.

Conocimientos

Python proficiency

PyTorch experience

Hugging Face Transformers

Transformer architectures

Model fine-tuning

Inference workflows

Evaluation methodologies

Prompt engineering

Git and GitHub

Codebase navigation

Herramientas

PyTorch

Hugging Face Transformers

GitHub

Descripción del empleo

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Engineer based in India.

As a Machine Learning Engineer, you will contribute to the development, improvement, and evaluation of modern machine learning systems, with a particular focus on Large Language Models (LLMs) and transformer-based architectures. You will work with existing machine learning codebases, analysing their structure and implementing practical enhancements to improve model performance and reliability. Using Python, PyTorch, and Hugging Face Transformers, you will support model fine-tuning, inference, and evaluation across a range of AI projects. You will also explore prompt engineering techniques and investigate model behaviour to identify opportunities for optimization. This role offers the opportunity to work on advanced AI initiatives involving real-world machine learning challenges. With a flexible, fully remote, part-time arrangement, you can contribute independently while collaborating on innovative AI development projects.

Accountabilities:

• Understand existing ML systems: Review and navigate established machine learning codebases to understand their architecture, functionality, dependencies, and implementation details.
• Develop and improve ML implementations: Write, modify, debug, and optimize machine learning solutions using Python and frameworks such as PyTorch.
• Work with modern AI architectures: Implement and support transformer-based models and LLM applications using Hugging Face Transformers and related technologies.
• Support model fine-tuning: Apply fine-tuning techniques to adapt existing models to specific tasks, improve their performance, and enhance output quality.
• Perform model inference and evaluation: Run experiments and evaluate model accuracy, performance, consistency, and overall effectiveness using appropriate evaluation methodologies.
• Apply prompt engineering: Design and refine prompts and explore model adaptation techniques to improve responses and task‑specific behaviour.
• Troubleshoot technical challenges: Investigate model-related issues, debug implementation problems, identify performance gaps, and recommend practical improvements.
• Manage development workflows: Use Git and GitHub for version control, code collaboration, code reviews, and maintaining organized development processes.
• Document technical findings: Record implementation changes, evaluation results, technical decisions, and relevant findings to support project continuity and knowledge sharing.

Requirements:

• Professional experience: At least 2 years of experience in Machine Learning Engineering, Applied Machine Learning, AI Engineering, or a related technical discipline.
• Python proficiency: Strong hands‑on programming skills in Python, with the ability to develop, debug, and maintain machine learning applications.
• Machine learning frameworks: Practical experience with PyTorch or comparable machine learning frameworks.
• LLM expertise: Experience working with Hugging Face Transformers and modern Large Language Models.
• Model architecture knowledge: Strong understanding of transformer‑based architectures and the principles behind modern machine learning systems.
• Fine‑tuning and inference: Practical knowledge of model fine‑tuning, inference workflows, and techniques for adapting models to specific requirements.
• Evaluation capabilities: Familiarity with model evaluation methodologies and the ability to assess accuracy, performance, and output quality.
• Prompt engineering: Understanding of prompt design and optimization techniques for improving LLM behaviour and task‑specific results.
• Codebase navigation: Ability to independently read, understand, navigate, and modify existing machine learning codebases.
• Version control: Experience using Git and GitHub for collaborative development, code management, and maintaining software quality.
• Analytical thinking: Strong debugging, critical thinking, and problem‑solving abilities, with attention to technical detail.
• Independent working style: Ability to manage assigned tasks autonomously, investigate unfamiliar implementations, and deliver reliable technical improvements.

Benefits:

• Competitive hourly compensation: Earn between USD 30 and USD 80 per hour, depending on experience, skills, and technical expertise.
• Flexible part‑time commitment: Approximately 10–15 hours per week, allowing you to balance this opportunity with other professional or personal commitments.
• Fully remote work: Work from anywhere in India without location‑based office requirements.
• Advanced AI exposure: Contribute to projects involving modern machine learning systems, LLMs, and transformer‑based architectures.
• Practical engineering experience: Apply your technical expertise to real‑world model development, fine‑tuning, debugging, and evaluation challenges.
• Professional development: Strengthen your experience with cutting‑edge AI technologies, tools, and machine learning methodologies.
• Meaningful contribution: Support initiatives focused on improving the development, quality, and evaluation of advanced AI systems.