Remote | Machine Learning & NLP Research Evaluator - $75-$105/hour

About the job Remote | Machine Learning & NLP Research Evaluator - $75-$105/hour

We are sharing a specialised part-time consulting opportunity for machine learning and natural language processing professionals experienced in model development, language understanding, retrieval systems, transformer architectures, Python workflows, and advanced AI evaluation.

This role supports a remote collaboration focused on improving how advanced AI systems reason across machine learning and natural language processing tasks. Selected professionals will apply their technical expertise to design realistic ML and NLP problems, develop rigorous reference solutions, evaluate model behavior, identify capability gaps, and contribute to high-quality technical assessment workflows.

Key Responsibilities

Machine Learning & NLP Task Development

Design challenging, real-world machine learning and NLP problems based on applied industry, research, or open-source experience
Develop tasks involving model training, language understanding, text generation, retrieval, classification, ranking, and applied ML pipelines
Create problems that target specific technical weaknesses in advanced AI systems
Calibrate task difficulty, expected behavior, and evaluation criteria against modern ML and NLP standards
Reference Solution & Evaluation Environment Creation

Develop clear specifications, reference solutions, and supporting technical materials
Prepare executable tests, validation logic, and evaluation components using Python where applicable
Integrate tasks into structured development and assessment environments
Review reference implementations for correctness, reproducibility, and technical quality
Model Performance Evaluation

Evaluate model outputs across machine learning, natural language processing, retrieval, generation, and agentic workflows
Assess outputs for correctness, robustness, consistency, and alignment with task requirements
Identify failures involving reasoning, implementation, data handling, model behavior, or language interpretation
Document evaluation decisions clearly and support findings with technical evidence
Capability Gap Analysis

Identify tasks where meaningful model-performance headroom remains
Classify technical failures according to their underlying cause, severity, and impact
Distinguish between reasoning errors, modeling limitations, implementation issues, and evaluation constraints
Collaborate with other subject-matter experts to maintain consistent and accurate assessment standards
Ideal Profile

Strong candidates may have:

Deep hands-on experience in machine learning or natural language processing through industry work, academic research, graduate study, or open-source contributions
Practical proficiency in Python used in research, production, or technical development environments
Strong understanding of modern ML and NLP methods, including model training, evaluation, and transformer-based systems
Experience with large language models, retrieval systems, language generation, or applied machine learning pipelines
Ability to design technically rigorous tasks and analyze model behavior independently
Strong written communication and time-management skills
Availability to contribute approximately 20 hours per week
Current location in the United States
Educational Background

A degree in computer science, machine learning, artificial intelligence, computational linguistics, data science, mathematics, or a related technical field is helpful
Graduate-level research or doctoral training in machine learning, NLP, artificial intelligence, or a related discipline is highly relevant
Professional experience developing or evaluating production ML or NLP systems is also highly valuable
Equivalent hands-on experience through established open-source, research, or applied technical contributions may be considered
Nice to Have

Experience with PyTorch, TensorFlow, JAX, Hugging Face, or comparable machine learning frameworks
Familiarity with transformers, large language models, embeddings, retrieval-augmented generation, or sequence modeling
Experience building datasets, benchmarks, evaluation harnesses, or reproducible ML pipelines
Knowledge of standard machine learning and NLP metrics, error-analysis methods, and validation practices
Experience with information retrieval, text classification, semantic search, summarization, or language generation
Previous involvement in AI training, model evaluation, technical benchmarking, or structured data review
Open-source contributions related to machine learning, NLP, evaluation tooling, or model infrastructure
Why This Opportunity

Apply advanced machine learning and NLP expertise to structured remote work
Contribute to the development of stronger language reasoning and model evaluation systems
Design realistic tasks aligned with your technical specialization and practical experience
Use your ability to identify subtle model failures and assess complex technical outputs
Participate in flexible, high-impact technical work with competitive hourly compensation
Contract Details

Part-time W-2 contingent employment arrangement
Fully remote within the United States
Expected commitment of approximately 20 hours per week
Competitive rates between $75-$105 per hour depending on experience, technical depth, and project scope
Role-based engagement involving collaboration with technical experts and evaluation teams
Work schedules and engagement details may be adjusted depending on scope, performance, and business needs
Work will not involve access to confidential or proprietary information from any employer, client, or institution

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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