Remote | Machine Learning & NLP Research Specialist — $75–$105/hour

We are sharing a specialised part-time consulting opportunity for US-based machine learning and natural language processing professionals with hands-on experience in Python, model training and evaluation, transformers, large language models, retrieval systems, and applied ML pipelines.

This role supports an advanced AI initiative focused on identifying reasoning and capability gaps in frontier models. Selected professionals will design challenging real-world ML and NLP tasks, develop executable reference solutions, evaluate model performance, and analyse failures across language understanding, generation, retrieval, training workflows, and applied machine learning systems.

Key Responsibilities

ML & NLP Task Development

• Design challenging machine learning and natural language processing problems based on practical research or industry experience
• Create tasks involving model training, evaluation, language understanding, generation, retrieval, or applied ML pipelines
• Target specific reasoning, implementation, and capability gaps in advanced AI models
• Define clear specifications, expected behaviour, constraints, datasets, and evaluation criteria

Reference Solutions & Python Development

• Develop accurate reference solutions and supporting materials using Python
• Integrate tasks into agent-based development and evaluation environments
• Create executable tests, validation scripts, scoring logic, or model pipelines where appropriate
• Ensure reference implementations are technically sound, reproducible, and appropriately challenging

Model Evaluation & Failure Analysis

• Evaluate model and agent performance across assigned ML and NLP tasks
• Compare generated outputs with reference solutions and expected results
• Identify tasks where models demonstrate meaningful limitations or inconsistent behaviour
• Classify failures involving reasoning, implementation, retrieval, language understanding, generation, or instruction adherence
• Document findings through clear and technically detailed written analysis

Quality Calibration & Collaboration

• Review tasks and evaluation methods developed by other machine learning specialists
• Maintain consistent standards for difficulty, accuracy, realism, and technical quality
• Participate in calibration and peer-review activities
• Collaborate with other subject matter experts to improve evaluation coverage and reliability

Ideal Profile

Strong candidates may have:

• Deep hands-on experience in machine learning, natural language processing, or both
• Practical proficiency in Python demonstrated through professional, academic, or open-source work
• Strong understanding of modern ML and NLP methods, including transformers and large language models
• Experience with model training, fine-tuning, evaluation, retrieval, or production ML pipelines
• Familiarity with PyTorch, TensorFlow, JAX, Hugging Face, or comparable frameworks and tooling
• Ability to design realistic technical problems and develop complete reference solutions
• Strong written communication and the ability to explain complex model behaviour clearly
• Reliable availability for approximately 20 hours per week

Educational Background

• A degree in computer science, machine learning, artificial intelligence, computational linguistics, data science, or a related technical field is highly relevant
• Graduate or doctoral research in machine learning, NLP, language modelling, information retrieval, or related areas may be especially valuable
• Equivalent professional experience in applied ML or NLP may also be considered
• Published research, open-source contributions, or production ML work may strengthen an application

Nice to Have

• Experience with transformer architectures, large language models, fine-tuning, or alignment methods
• Background in information retrieval, embeddings, reranking, search, or retrieval-augmented generation
• Experience with text classification, sequence modelling, summarisation, translation, or language generation
• Familiarity with benchmark design, model evaluation, error analysis, or adversarial testing
• Experience building executable technical assessments or automated evaluation pipelines
• Previous involvement in AI training, model evaluation, data annotation, or quality-review programmes
• Familiarity with agent-based development environments and structured technical rubrics

Why This Opportunity

• Apply advanced machine learning and NLP expertise to frontier AI evaluation
• Design realistic tasks grounded in practical research and engineering experience
• Analyse how modern models perform across language understanding, generation, retrieval, and applied ML workflows
• Help identify meaningful capability gaps and opportunities for model improvement
• Work remotely with a focused part-time commitment and competitive hourly compensation

Contract Details

• Part-time W-2 contingent employment arrangement
• Fully remote role available to candidates based in the United States
• Expected commitment of approximately 20 hours per week
• Competitive rates between $75–$105 per hour depending on expertise and project scope
• Working proficiency in Python is required
• Work may include onboarding, technical calibration, task development, model evaluation, and peer review
• Project scope, workload, and duration may be adjusted according to programme requirements and performance

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

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