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Machine Learning Expert – AI Training Project

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Remote

Machine Learning Expert – AI Training Project

Vikasnagar labs

Machine Learning Expert – AI Training Project

Skills

Deep LearningPythonNumPyPyTorchMachine LearningAI

1 month ago

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Important information


Contract type:

Freelance / Contract

Location:

India

Work mode:

Remote

Published on:

14 September 2026

What they need


Machine Learning Expert – AI Training Project

Compensation: ₹9,000–₹14,000 per hour
Location: Fully Remote
Job Type: Freelance | Approximately 15 hours per week
Schedule: Flexible – choose your own working hours and days

About the Opportunity

We are looking for highly skilled Machine Learning Experts to contribute to an advanced AI Training Project focused on machine learning engineering, model development, training and inference systems, numerical computing, performance optimization, and Python programming.

This opportunity is suitable for experienced Machine Learning Engineers, AI Engineers, Deep Learning Engineers, and Machine Learning Researchers with strong technical and engineering expertise. Candidates should be comfortable working beyond high-level APIs and solving complex machine learning and systems-level challenges.

Key Responsibilities

  • Develop, test, and validate machine learning models, training pipelines, and inference systems.
  • Build data pipelines, evaluation frameworks, benchmarking systems, and numerical methods.
  • Implement machine learning components using Python and command-line tools.
  • Work with tensor operations, automatic differentiation, model architectures, tokenization, batching, and text generation.
  • Optimize ML workloads for latency, throughput, memory usage, and hardware utilization.
  • Debug numerical instability, tensor-related issues, memory bottlenecks, and distributed-system failures.
  • Identify and resolve performance regressions and system-level failures.
  • Review, evaluate, and validate AI-generated code and technical solutions.
  • Design tests, benchmarks, and objective verification criteria.
  • Ensure technical solutions are accurate, reproducible, efficient, and production-ready.
  • Document technical decisions, implementation approaches, limitations, and performance trade-offs.

Required Qualifications

  • Master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a related quantitative discipline.
  • Strong professional or research experience in Machine Learning or Artificial Intelligence.
  • Strong Python programming skills.
  • Practical experience with at least two machine learning frameworks, libraries, or inference tools.
  • Strong understanding of model training, evaluation, inference, numerical computation, and optimization.
  • Ability to debug machine learning systems beyond basic API-level usage.
  • Experience developing reproducible technical workflows.
  • Ability to clearly explain implementation decisions, performance trade-offs, and technical failure modes.

Relevant Technologies

Experience with any of the following is highly relevant:

PyTorch, JAX, NumPy, SciPy, SGLang, vLLM, llama.cpp, Hugging Face Transformers, Hugging Face Tokenizers

Equivalent technologies may also be considered where candidates demonstrate strong technical depth and relevant experience.

Preferred Background

Experience working at a technology company, AI laboratory, research organization, or recognized engineering environment is preferred.

Candidates with exceptional open-source contributions, academic research, publications, or advanced independent machine learning projects may also be considered.

Key Skills

Machine Learning, Artificial Intelligence, AI Engineering, Deep Learning, Python, Model Training, Model Inference, Large Language Models, LLMs, Numerical Computing, Machine Learning Optimization, PyTorch, JAX, Hugging Face, Distributed Systems, Performance Engineering, AI Code Evaluation, Model Evaluation, ML Systems, Inference Optimization.

Pay: ₹9,000.00 - ₹14,000.00 per hour

Expected hours: 20.0 per week

Work Location: Remote

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