Key Strengths

Extensive personal project portfolio demonstrating strong interest and hands-on experience in AI/ML, particularly in areas like semantic caching, reinforcement learning, agent evaluation, and various predictive models.
Experience with diverse AI/ML applications including database integration (NexumDB), agent evaluation (agentunit), and traditional ML tasks (stock prediction, disease detection, emotion recognition).
Proficiency in Python, a core language for AI/ML development, and exposure to Rust for performance-critical components.
Demonstrated ability to work on complex, multi-technology projects (e.g., NexumDB combining SQL, AI, Rust, Python).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's extensive personal project work, particularly open-source initiatives like NexumDB and agentunit, suggests a proactive, self-driven individual with a strong passion for innovation and contributing to the technical community. This aligns well with a culture that values initiative and continuous learning. The breadth of projects indicates adaptability and a willingness to explore diverse problem domains within AI/ML.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The candidate's experience is primarily through personal projects, and no psychometric or English test results are available.

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Aviral Garg

Principal AI/ML Researcher and Engineer

https://www.opentalent.in/aviral-garg

GSoC'26 @apache | Co-Founder @Waysorted | Former DRDO Intern | AI/ML Developer and Researcher

@Waysorted-s-Organisation

New Delhi, IndiaMember since June 12, 2026

https://www.opentalent.in/aviral-garg

Top Skills

RustPythonShellDockerfiletypescriptHTMLJavaScriptJupyter Notebook

Skills

RustPythonShellDockerfiletypescriptHTMLJavaScriptJupyter Notebook

Experience

@Waysorted-s-Organisation

Principal AI/ML Researcher and Engineer

June 12, 2026 – Present

Projects

NexumDB

November 25, 2025 – Present

An innovative, open-source database that combines traditional SQL with AI-powered features including semantic caching and reinforcement learning-based query optimization.

View Project

agentunit

September 29, 2025 – Present

AgentUnit is a pytest-inspired evaluation harness for autonomous agents and retrieval-augmented generation (RAG) workflows. It helps you describe repeatable scenarios, connect them to your agent stack, and score results with both heuristic and LLM-backed metrics.