LLM Inference & AI Systems • Serving Engines • KV-Cache • GPU Kernels • C++ • CUDA • Triton
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
ramayan-audio
June 17, 2026 – Present
Pre-rendered Ramayan Hindi audio (Divya), served via jsDelivr
View Projectbreccia
May 23, 2026 – Present
Block-scaled FP8 / FP4 / INT4 tensor primitive with Triton scaled-matmul at FP32 parity on H100. NumPy / PyTorch / MLX / JAX backends.
View Projectscree
May 23, 2026 – Present
Variable-length tensors with Triton kernels at 1.6× of FlashAttention-2 on H100. NumPy / PyTorch / MLX / JAX backends.
View Projectstream-md
March 30, 2026 – Present
Streaming markdown for LLMs. 300x fewer chars parsed per token.
View ProjectCultural Fit Analysis
The candidate's personal projects show a diverse range of interests, from frontend technologies (TypeScript, CSS, JavaScript, HTML) to backend/AI/ML (Python, Dockerfile). This breadth suggests adaptability and a willingness to explore different domains. However, the target role is 'Frontend Developer', and while some projects align, many lean towards AI/ML or general backend. This indicates a potential fit if the role allows for cross-functional contributions or if the candidate can demonstrate deeper frontend expertise during interviews. The lack of professional experience or detailed project descriptions makes it difficult to fully assess alignment with a collaborative team environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided. Project descriptions are brief, limiting insight into collaboration or problem-solving approaches.