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

Job description

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