Machine Learning & NLP Expert

Posted 7 Hours Ago
Hiring Remotely in United States
Remote
80-110 Hourly
Senior level
Artificial Intelligence • HR Tech • Professional Services • Software
The Role
Design real-world ML and NLP tasks, build reference solutions and evaluation frameworks in Python, assess LLM outputs for correctness and reasoning, identify failure modes, create scoring rubrics, and collaborate with experts to improve model capabilities. Part-time, remote contractor (~20 hours/week).
Summary Generated by Built In

This role is for one of our clients

Compensation: $80-$110 per hour

Join a cutting-edge AI research initiative and help shape the next generation of frontier AI models. We are seeking experienced Machine Learning & NLP Experts to contribute their technical expertise toward training and evaluating advanced AI systems. In this role, you will design challenging, real-world machine learning and natural language processing tasks, create high-quality reference solutions, and assess AI model performance to identify reasoning gaps and improve overall capabilities.

This is a part-time, fully remote opportunity requiring approximately 20 hours per week.


RequirementsKey Responsibilities
  • Design challenging, real-world machine learning and natural language processing tasks covering areas such as:
    • Machine Learning Model Development and Evaluation
    • Natural Language Understanding (NLU)
    • Natural Language Generation (NLG)
    • Information Retrieval and Search
    • Applied Machine Learning Pipelines
    • Transformer Models and Large Language Models (LLMs)
  • Develop accurate reference solutions and integrate tasks into agentic development environments using Python.
  • Build executable evaluation frameworks and testing components where appropriate.
  • Evaluate AI model outputs for technical correctness, reasoning quality, and overall performance.
  • Identify capability gaps, classify model failure modes, and provide detailed written analyses.
  • Create and refine evaluation guidelines, scoring rubrics, and quality standards for ML and NLP tasks.
  • Collaborate with fellow subject matter experts to ensure consistency, accuracy, and high-quality training data.
Required Qualifications
  • Deep hands-on experience in Machine Learning and/or Natural Language Processing through industry, research, or graduate/PhD-level work.
  • Strong proficiency in Python with practical experience developing ML or NLP applications.
  • Strong understanding of modern machine learning techniques, including:
    • Model Training and Evaluation
    • Transformer Architectures
    • Large Language Models (LLMs)
    • NLP Pipelines
    • Feature Engineering and Model Optimization
  • Experience with industry-standard frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, or equivalent.
  • Ability to commit approximately 20 hours per week.
  • Excellent written communication skills and the ability to work independently in a remote environment.
Preferred Qualifications
  • Experience in AI model evaluation, AI training data creation, or human-in-the-loop model assessment.
  • Familiarity with Retrieval-Augmented Generation (RAG), vector databases, embedding models, or multimodal AI systems.
  • Experience building benchmarking frameworks, automated evaluation pipelines, or testing infrastructure.
  • Contributions to open-source ML/NLP projects or published research are a plus.
  • Experience working with production-scale machine learning systems.
Role Details
  • Employment Type: Independent Contractor
  • Work Arrangement: Fully Remote
  • Schedule: Approximately 20 hours per week
  • Project Duration: Based on project requirements and performance, with opportunities for extension
Equal Opportunity

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

Contract & Payment Terms
  • You will be engaged as an independent contractor.
  • This is a fully remote role that can be completed on your own schedule.
  • Projects may be extended, shortened, or concluded early depending on business needs and performance.
  • Your work will not involve access to confidential or proprietary information from any employer, client, or institution.
  • Payments are made weekly via Stripe or Wise based on services rendered.
  • Please note: We are unable to support H1-B or STEM OPT candidates at this time.

Skills Required

  • Deep hands-on experience in Machine Learning and/or Natural Language Processing via industry, research, or graduate/PhD-level work
  • Strong proficiency in Python with practical experience developing ML or NLP applications
  • Strong understanding of model training and evaluation, transformer architectures, LLMs, NLP pipelines, feature engineering, and model optimization
  • Experience with PyTorch, TensorFlow, Hugging Face Transformers, or equivalent frameworks
  • Ability to commit approximately 20 hours per week
  • Excellent written communication skills and ability to work independently in a remote environment
  • Experience in AI model evaluation, AI training data creation, or human-in-the-loop model assessment
  • Familiarity with Retrieval-Augmented Generation (RAG), vector databases, embedding models, or multimodal AI systems
  • Experience building benchmarking frameworks, automated evaluation pipelines, or testing infrastructure
  • Contributions to open-source ML/NLP projects or published research
  • Experience working with production-scale machine learning systems
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The Company
Year Founded: 2021

What We Do

Weekday is an AI-powered recruitment platform that helps startups hire top-tier engineering and product talent. By leveraging a massive database of white-collar professionals and advanced outreach tools, the company streamlines the hiring process through automated sourcing, AI-driven resume screening, and white-glove contingency services. Their mission is to modernize recruitment by enabling companies to discover and engage passive candidates efficiently, ensuring high-quality hires for critical roles.

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