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Open nowFirst seen 5 days ago

Remote | Member of Technical Staff, Enterprise AI — $300,000–$700,000/year

24-MAG343 open roles

Pay
$300,000 – $700,000 a year
Where
New York, United States, Remote
Work mode
Remote
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Your applicationOpen nowRemote | Member of Technical Staff, Enterprise AI — $300,000–$700,000/year24-MAG · New York, United States, Remote

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. 24-MAG postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: first seen 5 days ago

24-MAG median: 1 days open

The posting

We are sharing a specialised full-time opportunity for experienced technical professionals to operate at the intersection of enterprise AI, applied research, machine-learning evaluation, and real-world AI system performance.

Selected professionals will work directly within enterprise AI workflows to identify real-world failure modes, design high-signal datasets and evaluation frameworks, and run rapid experimental cycles that improve system performance. The role combines forward-deployed research, ML-oriented data design, agentic workflow evaluation, technical analysis, and close collaboration across research, product, domain, and enterprise teams.

Key Responsibilities

Enterprise AI Research & Failure Analysis

  • Embed within enterprise AI workflows as a technical research collaborator
  • Work alongside domain experts and enterprise teams to understand real-world system behaviour
  • Identify, formalise, and prioritise failure modes emerging from deployed AI systems
  • Translate operational issues into structured research questions and measurable technical problems
  • Produce clear analyses of system behaviour, limitations, and opportunities for improvement

ML-Oriented Data & Evaluation Design

  • Design high-signal datasets targeting identified model and system weaknesses
  • Develop evaluation protocols, quality criteria, and structured assessment frameworks
  • Apply strong judgement to data selection, evaluation design, and research-signal quality
  • Identify gaps in existing datasets and evaluation coverage
  • Structure research workflows to support measurable improvements in model performance

Experimentation & Agentic Workflow Evaluation

  • Run rapid experimental cycles to test hypotheses and quantify system improvements
  • Develop and benchmark agentic workflows with a focus on robustness, reliability, and scalability
  • Evaluate AI systems operating across complex enterprise workflows
  • Analyse experimental results and determine whether observed improvements are meaningful and reproducible
  • Iterate on datasets, evaluations, and system configurations based on research findings

Research Tooling & Cross-Functional Collaboration

  • Build lightweight tooling to support evaluation, data curation, experimentation, and rapid iteration
  • Collaborate across research, engineering, product, domain, and enterprise-facing teams
  • Translate research findings into clear, decision-oriented recommendations
  • Contribute to research artifacts including reports, benchmarks, evaluation documentation, and technical analyses
  • Communicate complex findings clearly to both technical and non-technical stakeholders

Ideal Profile

  • Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a closely related technical discipline
  • Strong judgement regarding research-signal quality, data selection, and evaluation design
  • Experience designing datasets, evaluation frameworks, or QA processes for machine-learning systems
  • Ability to translate ambiguous operational issues into structured research and evaluation problems
  • Familiarity with reinforcement-learning environments, agentic systems, or AI-system evaluation
  • Strong analytical skills and ability to produce concise, actionable technical insights
  • Proven ability to execute effectively within rapid iteration cycles and high-ambiguity environments
  • Strong written and verbal communication skills
  • Collaborative experience across research, product, engineering, and domain teams
  • Client-facing experience within technical or research-focused environments is advantageous
  • Experience building internal research or evaluation tooling is beneficial
  • Contributions to benchmarks, research publications, or open research initiatives are advantageous
  • Exposure to enterprise AI deployments or forward-deployed research environments is strongly valued

Engagement Details

  • Full-time engagement
  • Fully remote
  • Compensation: $300,000–$700,000/year
  • Work will span enterprise AI research, evaluation design, ML-oriented data systems, experimentation, and agentic workflow analysis
  • Responsibilities will involve direct collaboration with research, product, technical, domain, and enterprise stakeholders
  • Research priorities, datasets, evaluation frameworks, and system requirements may evolve based on experimental findings and deployment needs
  • Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party

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.

By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy

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