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Engineering intelligent systems ML, computer vision, edge, IoT, and scalable data pipelines.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
veccompact
June 15, 2026 – Present
Embedding index compaction for RAG vector stores. LSH-based near-duplicate detection and cluster merging, achieving 75% index size reduction with 81.7% faster search and perfect retrieval diversity.
View Projectmlpskim
June 14, 2026 – Present
Predictive activation sparsity engine for transformer MLP acceleration. SVD-based neuron prediction skips 67.6% of FLOPs with 0.9998 cosine similarity to dense output.
View Projectconfllm
June 13, 2026 – Present
Distribution-free prediction sets for LLM classification using conformal prediction. Split conformal, Mondrian, and adaptive prediction sets with four nonconformity scores, achieving 91.1% coverage (vs 71.7% argmax baseline) with formal guarantees.
View Projectcommitrisk
June 12, 2026 – Present
Statistical commit risk scoring for code review prioritization. SZZ-based bug labeling, 15-feature gradient boosted classifier, 2.2x precision lift over random baseline.
View Projectinjectguard
June 11, 2026 – Present
Statistical prompt injection detection for LLM applications. Ensemble of 10 heuristic features with calibratable weights, achieving 96% recall at 89% precision in under 100 microseconds per check. No model calls required.
View Projectconfgeo
June 10, 2026 – Present
Confidence geometry scoring for LLM reasoning trace selection. Extracts geometric features from token-level confidence trajectories and uses them to improve answer selection over majority voting, with +13.7pp overall and +41.2pp on hard problems.
View Projectspecroll
June 9, 2026 – Present
Speculative rollout engine for RL training acceleration. Draft-then-verify speculation reduces policy forward calls by 63-86%, accelerating RLHF/GRPO/PPO rollout generation.
View Projectschemapatch
June 8, 2026 – Present
Schema-guided JSON repair for LLM structured output. Two-pass repair engine (syntax + semantic) fixes malformed model responses using target JSON Schema constraints, achieving 96.3% schema validation on corrupted LLM output vs 8.3% without repair.
View Projectioteverythin-display
April 12, 2026 – Present
Touch-i: A wall-mounted Home Assistant control panel on the Waveshare ESP32-S3-Touch-LCD-4. Switches, Climate, Media, Presence. HACS integration with zero-code setup.
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards AI/ML research and development, primarily using Python. While this demonstrates deep technical capability in a specific area, the lack of diverse project types (e.g., large-scale distributed systems, traditional backend services) and formal team experience makes it challenging to assess cultural fit for a general 'Backend Engineer' role. The focus on personal, research-oriented projects might indicate a preference for individual contribution over collaborative team environments, which could be a cultural fit consideration depending on the team's dynamics.
Soft Skills & Operational Fit
The candidate's extensive personal projects suggest strong self-motivation, problem-solving abilities, and a proactive approach to learning and development. However, without formal work experience or psychometric test results, it is difficult to assess stress handling, team collaboration, or other operational fit aspects.