PhD Machine Learning Research Scientist

24-MAG

Part-time ML research scientist advancing frontier algorithms for 24-MAG’s remote consulting platform. Designing experiments, evaluating methods, and reviewing research outputs across reinforcement learning and AI for science.

Posted 8/5/2026part-timeRemote • New York • 🇺🇸 United StatesMid-LevelSenior💰 $105 - $140 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in advanced machine learning methods, algorithmic innovation, and experimental design, with a strong emphasis on rigorous scientific reasoning and technical writing. Capable of collaborating with researchers and stakeholders while maintaining high scientific standards in research outputs.

Highest-signal resume keywords

PhD In Machine LearningOriginal Contributions To Machine LearningMain-Conference Publication At ICML, NeurIPS, Or ICLRStrong Experimental DesignTechnical Writing Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Advanced Machine Learning MethodsAlgorithmic ApproachesStatistical MethodologyExperimental DesignReproducible Research WorkflowsPerformance EvaluationMathematical ReasoningResearch DocumentationTechnical ReviewFeedback Provision

Soft Skills

Independent WorkCollaborationClear CommunicationProblem-SolvingCritical Thinking

Industry Keywords

Machine LearningArtificial IntelligenceComputer ScienceStatisticsApplied MathematicsResearch ExperienceAlgorithmic InnovationResearch QualityExperimental AssumptionsResearch Standards

About the role

Key responsibilities & impact

Contribute to well-defined research problems involving advanced machine learning methods
Develop and evaluate original algorithmic approaches grounded in current research
Analyse experimental results and identify opportunities for improvement
Apply rigorous scientific reasoning to complex and open-ended technical questions
Design experiments testing novel learning strategies, architectures, or optimisation methods
Develop reproducible research workflows and document experimental assumptions
Evaluate competing approaches using appropriate metrics and statistical methodology
Diagnose unexpected behaviour, methodological weaknesses, and performance limitations
Review technical outputs for methodological soundness, originality, and research quality
Assess whether claims are supported by experiments and appropriate baselines
Identify gaps in reasoning, evaluation design, and interpretation of results
Provide precise written feedback and recommendations for further investigation
Collaborate asynchronously with senior researchers and technical stakeholders
Communicate findings, limitations, and research decisions clearly
Support fast project execution while maintaining high scientific standards

Requirements

What you’ll need

PhD in machine learning, computer science, artificial intelligence, statistics, applied mathematics, or a closely related discipline is required
Doctoral research demonstrating substantial original contributions to machine learning
At least one main-conference publication at ICML, NeurIPS, or ICLR
Demonstrated experience conducting original machine learning research
Record of contributing to algorithmic innovation rather than primarily applied analytics
Strong experimental design, mathematical reasoning, and technical writing skills
Ability to work independently on ambiguous and research-intensive problems
Availability to contribute promptly to an urgent pilot engagement
Additional research experience within a university, industrial research laboratory, or advanced AI organisation may strengthen an application

Benefits

Comp & perks

Fully remote with flexible scheduling
Competitive rates between $105–$140 per hour depending on research expertise and publication record
Weekly payments via Stripe or Wise
Potential project extensions depending on pilot outcomes, scope, and performance