Sushant Kumar
I’m Sushant Kumar, an AI Model Trainer focused on building high-quality training datasets by carefully annotating, tagging, and evaluating large-scale outputs—especially for video- and knowledge-retrieval style tasks.
About
I’m Sushant Kumar, an AI Model Trainer focused on building high-quality training datasets by carefully annotating, tagging, and evaluating large-scale outputs—especially for video- and knowledge-retrieval style tasks. I enjoy applying detailed grading guidelines, catching issues like hallucinations or factual inconsistencies, and keeping labeling consistent so model improvements translate into better real-world behavior.
Alongside training and evaluation work, I’ve also supported data reliability through engineering tasks—processing high-volume event streams with rigorous validation, and building monitoring/alerting to quickly surface anomalies. I’m detail-driven, strong in written communication, and comfortable collaborating with trainers and technical teams to resolve ambiguity and continuously improve quality across workflows.
- 1 year's experience
- Joined September 2026
Industry experience
- Software & Internet
- Computers & Electronics
- Education
- Media & Entertainment
Work experience· 4 roles
Managed 15+ real-time Apache Flink/Spark jobs processing 100K+ events/sec, applying rigorous data validation and quality checks to ensure accuracy across high-volume pipelines. Built monitoring and observability dashboards using Grafana and Prometheus to catch anomalies, and developed automated incident-reporting workflows with AWS Lambda and SNS. Strengthened time-sensitive documentation and clear written communication through incident and reporting processes.
Performed large-scale annotation and systematic evaluation of Google Gemini outputs across multiple domains (video/YouTube retrieval, messaging, utilities, productivity) using detailed grading guidelines. Tagged responses with consistent labeling, reviewed content to detect hallucinations, factual inaccuracies, and inconsistencies, and improved search relevance and ranking through granular, criteria-based review. Delivered structured, evidence-backed written feedback and collaborated with trainers and evaluators to resolve ambiguities. Used DataCompute and related tooling to benchmark model iterations and document findings.
Led outreach programs and workshops as a campus partner, using clear written and verbal communication to explain AI tools and drive adoption within the student community. Independently planned, organized, and coordinated multiple end-to-end events in a remote, deadline-driven environment. Shared structured feedback with the product team through consistent collaboration.
Education
Certifications and awards
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