CTGT

4 weeks ago

Research Intern: Interpretability & Reliability (Summer 2027)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Join CTGT as a research intern to tackle a core problem in model interpretability and reliability. You will design, implement, and evaluate methods for feature extraction and runtime intervention across model families, collaborate with engineers to ship a Policy Engine capability, and present weekly progress while contributing to high-stakes AI governance research.

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Seniority: Intern level

Key Responsibilities

•Implement and stress-test methods for feature extraction and runtime intervention, across model families, ensuring repeatable results.
•Design evaluations that bound error rather than average it, including calibration under imbalanced data and reasoning-trace grading.
•Read relevant literature to decide what matters, reproduce it, and push past it.
•Collaborate with engineering to turn findings into Policy Engine capabilities for audited, high-stakes environments.
•Present progress weekly and defend your reasoning.

Pay and Benefits

Salary: USD 8,000 - 12,000 annually

Key Requirements

•Pursuing a degree (Bachelor's through PhD) in computer science, mathematics, the sciences, or a quantitatively rigorous field.
•Strong mathematical foundations: linear algebra, probability, optimization, information theory.
•Ability to read a paper, decide what matters, and implement it.
•Experience writing real code for computational systems; fluency with PyTorch and the modern ML stack (or demonstrable progress toward it).
•Interest in interpretability, model internals, and building reliable systems; self-directed with minimal scaffolding.

Experience:Artificial intelligenceMachine learningResearch

Skills:Problem-solvingCommunicationCritical thinkingCollaborationSelf-direction

Tech Stack:PythonRustNodeTypeScriptReactPostgreSQLVector databasesGraph databasesDockerKubernetesTerraformGPUCloud computing

Eligibility

Work Authorization:Sponsorship available.

Company Brief

CTGT

CTGT builds AI-driven software solutions that leverage machine learning to automate data analysis, generate insights, and streamline decision-making for enterprise clients across industries. Their platform focuses on scalable AI tooling, model deployment, and workflow integration to boost operational efficiency.

Industry: AI & Machine Learning

Website

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CTGT

4 weeks ago

Research Intern: Interpretability & Reliability (Summer 2027)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Seniority: Intern level

Key Responsibilities

•Implement and stress-test methods for feature extraction and runtime intervention, across model families, ensuring repeatable results.
•Design evaluations that bound error rather than average it, including calibration under imbalanced data and reasoning-trace grading.
•Read relevant literature to decide what matters, reproduce it, and push past it.
•Collaborate with engineering to turn findings into Policy Engine capabilities for audited, high-stakes environments.
•Present progress weekly and defend your reasoning.

Pay and Benefits

Salary: USD 8,000 - 12,000 annually

Key Requirements

•Pursuing a degree (Bachelor's through PhD) in computer science, mathematics, the sciences, or a quantitatively rigorous field.
•Strong mathematical foundations: linear algebra, probability, optimization, information theory.
•Ability to read a paper, decide what matters, and implement it.
•Experience writing real code for computational systems; fluency with PyTorch and the modern ML stack (or demonstrable progress toward it).
•Interest in interpretability, model internals, and building reliable systems; self-directed with minimal scaffolding.

Experience:Artificial intelligenceMachine learningResearch

Skills:Problem-solvingCommunicationCritical thinkingCollaborationSelf-direction

Tech Stack:PythonRustNodeTypeScriptReactPostgreSQLVector databasesGraph databasesDockerKubernetesTerraformGPUCloud computing

Eligibility

Work Authorization:Sponsorship available.

Company Brief

CTGT

Industry: AI & Machine Learning

Website