全职 Annotation Research Scientist (AI-Autonomous) 工作, 薪水 up to SGD 15,000, DADACONSULTANTS PTE. LTD. West Region (Singapore) 公司招聘中 - Ricebowl

Annotation Research Scientist

Role Summary

As an Annotation Research Scientist, you will research and implement algorithmic approaches for large-scale data annotation, quality assessment, and AI-assisted production workflows. This role requires both research judgment and engineering execution: you should be able to evaluate algorithmic directions, design reliable benchmarks, and collaborate with data platform, engineering, and delivery teams to bring research ideas into stable production workflows.

Key Responsibilities

Research, evaluate, and implement automated or semi-automated annotation methods to improve data production efficiency and quality.

Design algorithm-assisted workflows for complex data types, including annotation support, quality assessment, anomaly detection, and review optimization.

Build evaluation frameworks, benchmarks, metrics, and error analysis methods to support data-driven algorithm selection.

Collaborate with data platform, algorithm, engineering, and operations teams to turn research prototypes into reusable and maintainable production workflows.

Analyze data quality issues and manual review bottlenecks, and propose practical approaches to improve efficiency and reliability.

Stay up to date with advances in computer vision, weak/semi-supervised learning, automated annotation, and multimodal understanding, and validate relevant ideas in real scenarios.

Requirements

Bachelor's degree or above in Computer Science, Artificial Intelligence, Electrical Engineering, Automation, Mathematics, or a related field; Master's or PhD preferred.

5+ years of experience in AI/CV/ML research or engineering. Experience with large-scale annotation, data quality, video understanding, multimodal data processing, or 3D perception is preferred.

Strong foundation in computer vision or machine learning, with hands-on depth in at least one area such as video understanding, human pose estimation, 3D reconstruction, weak/semi-supervised learning, or automated annotation.

Ability to independently investigate, reproduce, adapt, and evaluate algorithmic approaches, beyond simply reading papers.

Strong engineering mindset with the ability to integrate algorithm modules into real data workflows while considering stability, cost, maintainability, and scalability.

Proficiency in Python and common deep learning frameworks, with solid experiment management, data analysis, and result interpretation skills.

Strong independent research judgment, ownership, curiosity, and resilience, with the ability to drive validation and delivery in an early-stage startup environment.

Nice to Have

Experience deploying algorithms in large-scale video, multimodal, or spatial data production systems.

Experience in automated annotation, active learning, weak/semi-supervised learning, data quality evaluation, or manual review cost reduction.

Experience with robotics, embodied AI, industrial vision, AR/VR, or complex sensor data.

Publications, open-source projects, or strong technical output in CVPR / ICCV / ECCV / NeurIPS / ICLR / ICML or related venues.

Experience in AI data services, annotation platforms, AI infrastructure companies, or research labs.

Regret to inform that only shortlisted candidates will be notified.

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EA Registration Number: R1878287

Business Registration Number: 201735941W.

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