Machine Learning, NLP Expert

This is a fully remote position, open to applicants in United States.

📋 Description

• Become a part of an innovative AI research project and play a key role in developing the next generation of advanced AI models.

• Provide your technical expertise to train and assess sophisticated AI systems.

• Design complex, real-world tasks in machine learning and natural language processing.

• Produce high-quality reference solutions and evaluate AI model performance to detect reasoning deficiencies and enhance overall capabilities.

• Generate accurate reference solutions and embed tasks into agentic development environments using Python.

• Construct executable evaluation frameworks and testing components as necessary.

• Assess AI model outputs for technical accuracy, reasoning quality, and overall effectiveness.

• Identify capability deficiencies, categorize model failure modes, and provide comprehensive written analyses.

• Develop and refine evaluation protocols, scoring rubrics, and quality standards for ML and NLP tasks.

• Collaborate with other experts to ensure consistency, accuracy, and the delivery of high-quality training data.

⛳️ Requirements

• Extensive hands-on experience in Machine Learning and/or Natural Language Processing through industry work, research, or graduate/PhD-level studies.

• Strong command of Python with practical experience in developing ML or NLP applications.

• Solid understanding of contemporary machine learning methodologies, including:

• - Model Training and Evaluation

• - Transformer Architectures

• - Large Language Models (LLMs)

• - NLP Pipelines

• - Feature Engineering and Model Optimization

• Familiarity with industry-standard frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, or similar.

• Willingness to dedicate approximately 20 hours per week.

• Exceptional written communication skills and the capability to work independently in a remote setting.

• Preferred Qualifications

• Experience in AI model evaluation, AI training data generation, or human-in-the-loop model assessment.

• Knowledge of Retrieval-Augmented Generation (RAG), vector databases, embedding models, or multimodal AI systems.

• Experience in building benchmarking frameworks, automated evaluation pipelines, or testing infrastructure.

• Contributions to open-source ML/NLP initiatives or published research are advantageous.

• Experience with production-scale machine learning systems.

🏝️ Benefits

• Opportunity to work on cutting-edge technology in a rapidly evolving field.

• Collaborate with a team of experts and thought leaders in AI.

• Flexible working hours and the ability to work remotely.

• Engage in meaningful work that contributes to the future of AI development.