Member of Technical Staff, Enterprise AI

SaidGig; New York (NY); Remote; USD 180,000 - 700,000; Full time

Benefits offered by this job

Health-insurance reimbursement

Paid time off

401(k) plan with company match

Remote-first workforce

Job summary

SaidGig is seeking a forward-deployed research partner to collaborate with enterprise AI teams. You will help identify failure modes in live workflows, design robust datasets and evaluation protocols, and run rapid experiments to improve system performance.

The role emphasizes actionable insights and cross-functional collaboration across research, product, and domain teams. The position supports a remote-first setup with full-time commitment and equity options.

Qualifications

• Master’s degree or higher in a technical field.
• Strong judgment about research signal quality and evaluation design.
• Experience designing datasets and evaluation frameworks for ML systems.
• Ability to turn ambiguous issues into structured research problems.
• Familiarity with RL environments and agentic-system evaluation.
• Clear, concise communication and actionable insights.

Responsibilities

• Partner with domain experts and client teams in enterprise AI workflows.
• Identify, formalize, and prioritize failure modes observed in real deployments.
• Design high-signal datasets and evaluation protocols addressing weaknesses.
• Run rapid experiments to test hypotheses and measure improvements.
• Produce clear, decision-focused analyses of system behavior and performance.
• Develop and benchmark agentic workflows for robustness and scalability.
• Build lightweight tools for evaluation, data curation, and fast iteration.
• Contribute to research reports, benchmarks, and related materials.

Skills

Research design

RL familiarity

Communication

Cross-team collab

Data/evaluation quality

Rapid iteration

Problem structuring

Education

Master's degree in CS/ML/AI

Tools

Evaluation tools

Job description

Role Overview

Work as a forward-deployed research partner within enterprise AI systems, collaborating on live workflows to identify failure modes and rapidly improve system performance through research, evaluation, and experimentation.

Key Responsibilities

• Partner with domain experts and client teams within enterprise AI workflows.
• Identify, formalize, and prioritize failure modes observed in real-world deployments.
• Design high-signal datasets and evaluation protocols that address identified system weaknesses.
• Run rapid experiments to test hypotheses and measure improvements.
• Produce clear, decision-focused analyses of system behavior and performance.
• Develop and benchmark agentic workflows for robustness and scalability.
• Build lightweight tools for evaluation, data curation, and fast iteration.
• Contribute to research reports, benchmarks, and other internal or external research materials.

Qualifications

• Master''s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field.
• Strong judgment about research signal quality, including data selection and evaluation design.
• Experience designing datasets and evaluation frameworks for machine learning systems.
• Ability to turn ambiguous operational issues into structured research problems.
• Familiarity with reinforcement learning environments and/or agentic-system evaluation.
• Clear, concise communication skills and a focus on actionable insights.
• Demonstrated ability to work effectively through rapid iteration and ambiguity.
• Experience collaborating across research, product, and domain teams.

Preferred Qualifications

• Client-facing experience in technical or research-driven environments.
• Experience building internal research or evaluation tools.
• Contributions to benchmarks, research publications, or open research initiatives.
• Exposure to enterprise AI deployments or forward-deployed research models.

Work Terms

Full-time, remote role.

Compensation

• Listed annual compensation range: $300, 000 to $700, 000.
• National base-salary range: $180, 000 to $250, 000 USD annually.
• Eligible for equity compensation and, depending on role and company policies, performance-based bonuses.

Benefits

• up to 100% reimbursement for health-insurance premiums
• paid time off
• a 401(k) plan with company match
• additional benefits supporting a remote-first workforce

Eligibility

Qualified applicants are considered without regard to race, color, religion, sex, including pregnancy, sexual orientation, or gender identity, national origin, age, disability, genetic information, veteran status, or other characteristics protected by applicable law.

Application Process

Reasonable accommodation assistance is available during the application process.