ML Engineer - Remote

Yo Labs Inc.
New York, NY, United States
4 days ago
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Role details

Contract type
Contract
Employment type
Full-time (> 32 hours)
Working hours
Shift work

Tech stack

Artificial Intelligence Command-Line Interface Software Debugging Python (Programming Language) Machine Learning NumPy Open Source Technology Performance Tuning SciPy Pytorch AI Coding Agents Numerical Computing
+4 more
Information Technology HuggingFace SGLang Data Pipelines

Job description

  • Develop, implement, and validate machine learning models, training pipelines, and inference systems.
  • Build model components, data pipelines, evaluation frameworks, and numerical methods.
  • Create reproducible workflows using Python and command-line tools.
  • Debug numerical, performance, and system-level issues.
  • Optimize memory usage, throughput, and overall model performance.
  • Review and validate machine learning implementations against defined correctness and performance requirements.

Requirements

We are looking for highly skilled Machine Learning Engineers to contribute to an AI training project focused on model development, training and inference systems, numerical computing, performance optimization, and Python-based engineering.

This is a highly coding-intensive role. Candidates must have hands-on experience using Python and coding agents as part of their development workflow., * Master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative field.

  • Strong professional or research experience in machine learning.
  • Advanced practical proficiency in Python and coding agents.
  • Experience with one or more of the following:

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

  • Equivalent tools may also be considered where candidates demonstrate relevant technical depth.
  • Experience at a technology company, AI laboratory, research organization, or recognized engineering environment is preferred.
  • Strong open-source or academic experience may also qualify.

Benefits & conditions

Compensation is output-based, with payment provided per task that meets project specifications. Task completion time may vary depending on experience and workflow. Minimum submission requirements apply.

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