Vaishali Thakur

Software Engineer

Kangra, Himachal Pradesh, India0 mo experience

Key Highlights

Strong web development expertise demonstrated through impactful internships.
Proven project management skills showcased in academic and internship projects.
Active contributor to innovative tech solutions in collaborative environments.

Stackforce AI infers this person is a Software Engineer with a focus on SaaS and AI/ML technologies.

Contact

Skills

Core Skills

Software DevelopmentUi/ux DesignMachine LearningComputer Vision

Other Skills

JiraConfluenceStatsigSplunkMasked AutoencoderViTFacial Attribute RecognitionDeepfake DetectionFaceX-Zoo

About

Passionate Computer Science student at NIT Hamirpur with expertise in web development and software solutions. Intern at Imagine-her, contributing to the ticketX website. Also developing Convocation Portal with a team. Fellow'23 at DESIS Ascend Educare, showcasing strong project management skills in the TPO Portal project. Actively seeking opportunities in impactful tech projects.

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Mediatek

Software Engineer Intern

Jan 2026 – Present · 3 mos · Noida, Uttar Pradesh, India · On-site

Atlassian

Software Engineer Intern

May 2025 – Jul 2025 · 2 mos · Bengaluru, Karnataka, India · Remote

● Built inline reply functionality in Jira’s notification drawer, boosting replies per notification viewed by 3%
● Extended the feature to Confluence, integrating Jira related comment notifications for cross-product engagements
● Partnered with design team to finalize UI/UX & implemented components for editor, dialog & success indicators
● Used Statsig for experiments and metrics analysis, Splunk for proactive alert monitoring to ensure reliable rollouts
● Configured the feature gates with exposure points, including pre-analysis for runtime & sample size estimates

JiraConfluenceUI/UX DesignStatsigSplunkSoftware Development

Iit mandi

Research Intern

May 2024 – Jun 2024 · 1 mo · Mandi, Himachal Pradesh, India · On-site

Implemented masked autoencoder and ViT for self-supervised facial video representation learning model
Implemented a facial-region guided masking strategy with FaceX-Zoo to enhance facial feature learning
Leveraged the model for experiments on tasks like Facial Attribute Recognition and Deepfake Detection
Worked with diverse datasets like YouTube Face and CelebV-HQ, ensuring robust training and evaluation

Masked AutoencoderViTFacial Attribute RecognitionDeepfake DetectionFaceX-ZooMachine Learning+1