Member of Technical Staff, Enterprise AI
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Job Description
Enterprise AI researcher improving machine-learning evaluation, datasets, and agentic workflows for 24-MAG. Analyzing failure modes and experimental results across enterprise AI systems.
Responsibilities:
- 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 analyses of system behaviour, limitations, and opportunities for improvement
- Design high-signal datasets targeting model and system weaknesses
- Develop evaluation protocols, quality criteria, and structured assessment frameworks
- Identify gaps in existing datasets and evaluation coverage
- Run rapid experimental cycles to test hypotheses and quantify system improvements
- Develop and benchmark agentic workflows for robustness, reliability, and scalability
- Evaluate AI systems operating across complex enterprise workflows
- Analyse experimental results and determine whether improvements are meaningful and reproducible
- Iterate on datasets, evaluations, and system configurations based on research findings
- Build lightweight tooling for 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 reports, benchmarks, evaluation documentation, and technical analyses
- Communicate complex findings to technical and non-technical stakeholders
Requirements:
- 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
Benefits:
- Fully remote work arrangement
- Full-time engagement
- Compensation of $300,000–$700,000/year
- Remote consulting opportunities through 24-MAG LLC
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