Company: Evalixa AI Private Limited

Engagement Type: Freelance / Independent Contractor

Work Mode: Remote

Location: India

Schedule: Flexible and project-based To Apply: Send your resume and relevant details to [email protected] About Evalixa AI

Evalixa AI Private Limited is an AI benchmarking and evaluation company focused on developing challenging benchmarks, high-quality datasets, and reliable evaluation systems for frontier AI models.

We work on real-world technical environments designed to test how advanced AI systems perform across machine learning, software engineering, coding, reasoning, debugging, and long-horizon tasks. Role Overview

We are looking for experienced Machine Learning Engineers to work with us on ML-focused AI benchmarking and evaluation projects.

You’ll work with real-world machine learning problems involving datasets, model training, evaluation, inference pipelines, experiments, and ML codebases. The work requires a good mix of machine learning knowledge and practical software engineering skills.

This is a remote, project-based freelance opportunity. Work will be assigned based on project availability, technical expertise, performance, and quality. What You’ll Work On

Work with real-world machine learning codebases and ML environments.

Build, run, modify, and validate model training and evaluation pipelines.

Work with datasets, preprocessing pipelines, features, metrics, and model outputs.

Develop and validate challenging machine learning tasks for advanced AI models.

Train and evaluate models using up-to-date ML frameworks.

Debug ML pipelines, training failures, data issues, and incorrect model behaviour.

Evaluate AI-generated solutions for correctness, completeness, and reliability.

Identify failure cases, edge cases, and shortcuts taken by AI systems.

Review Python code, datasets, tests, configurations, and model outputs.

Create reliable tests and validation methods for ML tasks.

Improve existing ML tasks based on evaluation results and model performance.

Write clean, reproducible, and well-documented Python code.





Work with researchers, engineers, and reviewers to improve benchmark quality. Requirements

4+ years of experience as a Machine Learning Engineer, ML-focused Software Engineer, Data Scientist, or similar technical role.

Strong proficiency in Python.

Strong understanding of machine learning fundamentals.

Hands-on experience with model training, evaluation, and inference.

Experience with PyTorch, TensorFlow, JAX, Scikit-learn, or similar ML frameworks.

Experience working with datasets, data preprocessing, feature engineering, and evaluation metrics.

Ability to understand and modify existing ML codebases.

Good understanding of supervised and unsupervised learning, optimization, validation, and model evaluation.

Strong debugging and problem-solving skills.

Ability to write clean, maintainable, and reproducible code.

Comfortable working with Git and software development workflows.

Good written and verbal English communication skills.

Ability to independently understand and solve unfamiliar ML problems.

Preferred

Qualifications

Experience with deep learning and neural network architectures.

Experience with NLP, computer vision, recommendation systems, time-series modelling, or other ML domains.

Experience with Docker or containerized ML environments.

Experience working with GPUs and ML training infrastructure.

Familiarity with Linux and command-line environments.

Experience with experiment tracking and model evaluation tools.

Familiarity with Hugging Face, Transformers, or other modern ML ecosystems.

Experience with Kaggle-style machine learning problems or competitive ML is an advantage.

Familiarity with LLMs, AI agents, AI benchmarking,



or model evaluation is an advantage.

What We Look

For

We’re looking for engineers who enjoy solving difficult ML problems, experimenting with different approaches, debugging models and pipelines, and understanding why a solution works or fails.

You should be comfortable working with an existing ML project, understanding the data and evaluation setup, making changes to the code, running experiments, and validating the results.

The work is not limited to simply training models. A major part of the role involves creating and evaluating technical problems that can genuinely test the machine learning capabilities of advanced AI systems.

Freelancing With

Evalixa AI

Fully remote work.

Flexible, project-based engagement.

Work on challenging machine learning and AI benchmarking problems.

Opportunity to work with advanced AI models and agentic systems.

Exposure to real-world ML codebases, datasets, evaluation pipelines, and testing environments.

Work alongside engineers and researchers on frontier AI evaluation projects.

Offer

Details

Engagement Type: Freelance / Independent Contractor

Work Mode: Remote

Location: India

Schedule: Flexible and project-based

Duration: Based on project requirements

Work Allocation: Based on project availability, expertise, performance, and quality

Compensation: Project/task-specific compensation will be communicated before assignment.

Evaluation

Process

Selected candidates may complete a technical evaluation covering:

Python programming

Machine learning fundamentals

Data processing and analysis

Model training and evaluation

ML debugging and problem-solving

Understanding existing ML codebases

Practical machine learning tasks

Code quality and reproducibility The evaluation may include a technical discussion and/or practical coding or machine learning assessment. Candidates who successfully complete the evaluation may be onboarded as Freelance Machine Learning Engineers for relevant Evalixa AI projects.

📌 Machine Learning Engineer – AI Benchmarking (Hyderabad)
🏢 Evalixa AI
📍 Hyderabad