About the job Remote | Machine Learning & NLP Research Evaluator - $75-$105/hourWe 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 ResponsibilitiesMachine Learning & NLP Task DevelopmentDesign challenging, real-world machine learning and NLP problems based on applied industry, research, or open-source experienceDevelop tasks involving model training, language understanding, text generation, retrieval, classification, ranking, and applied ML pipelinesCreate problems that target specific technical weaknesses in advanced AI systemsCalibrate task difficulty, expected behavior, and evaluation criteria against modern ML and NLP standardsReference Solution & Evaluation Environment CreationDevelop clear specifications, reference solutions, and supporting technical materialsPrepare executable tests, validation logic, and evaluation components using Python where applicableIntegrate tasks into structured development and assessment environmentsReview reference implementations for correctness, reproducibility, and technical qualityModel Performance EvaluationEvaluate model outputs across machine learning, natural language processing, retrieval, generation, and agentic workflowsAssess outputs for correctness, robustness, consistency, and alignment with task requirementsIdentify failures involving reasoning, implementation, data handling, model behavior, or language interpretationDocument evaluation decisions clearly and support findings with technical evidenceCapability Gap AnalysisIdentify tasks where meaningful model-performance headroom remainsClassify technical failures according to their underlying cause, severity, and impactDistinguish between reasoning errors, modeling limitations, implementation issues, and evaluation constraintsCollaborate with other subject-matter experts to maintain consistent and accurate assessment standardsIdeal ProfileStrong candidates may have:Deep hands-on experience in machine learning or natural language processing through industry work, academic research, graduate study, or open-source contributionsPractical proficiency in Python used in research, production, or technical development environmentsStrong understanding of modern ML and NLP methods, including model training, evaluation, and transformer-based systemsExperience with large language models, retrieval systems, language generation, or applied machine learning pipelinesAbility to design technically rigorous tasks and analyze model behavior independentlyStrong written communication and time-management skillsAvailability to contribute approximately 20 hours per weekCurrent location in the United StatesEducational BackgroundA degree in computer science, machine learning, artificial intelligence, computational linguistics, data science, mathematics, or a related technical field is helpfulGraduate-level research or doctoral training in machine learning, NLP, artificial intelligence, or a related discipline is highly relevantProfessional experience developing or evaluating production ML or NLP systems is also highly valuableEquivalent hands-on experience through established open-source, research, or applied technical contributions may be consideredNice to HaveExperience with PyTorch, TensorFlow, JAX, Hugging Face, or comparable machine learning frameworksFamiliarity with transformers, large language models, embeddings, retrieval-augmented generation, or sequence modelingExperience building datasets, benchmarks, evaluation harnesses, or reproducible ML pipelinesKnowledge of standard machine learning and NLP metrics, error-analysis methods, and validation practicesExperience with information retrieval, text classification, semantic search, summarization, or language generationPrevious involvement in AI training, model evaluation, technical benchmarking, or structured data reviewOpen-source contributions related to machine learning, NLP, evaluation tooling, or model infrastructureWhy This OpportunityApply advanced machine learning and NLP expertise to structured remote workContribute to the development of stronger language reasoning and model evaluation systemsDesign realistic tasks aligned with your technical specialization and practical experienceUse your ability to identify subtle model failures and assess complex technical outputsParticipate in flexible, high-impact technical work with competitive hourly compensationContract DetailsPart-time W-2 contingent employment arrangementFully remote within the United StatesExpected commitment of approximately 20 hours per weekCompetitive rates between $75-$105 per hour depending on experience, technical depth, and project scopeRole-based engagement involving collaboration with technical experts and evaluation teamsWork schedules and engagement details may be adjusted depending on scope, performance, and business needsWork will not involve access to confidential or proprietary information from any employer, client, or institutionAbout the PlatformThis opportunity is available through 24-MAG LLC. 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