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ahmeddoghri/README.md

Ahmed Doghri

Senior AI Engineer β€” RAG, multi-agent orchestration, LLM evaluation, and MLOps. 8+ years shipping production LLM and ML systems in regulated domains (pharma / FDA, banking / fintech, B2B), plus the unglamorous data engineering that keeps them running in production instead of just in a demo.

I care about one thing in AI engineering: claims you can check. The systems below run end to end; the benchmarks regenerate their own numbers. No API keys, mystery services, or copied paper results. The same discipline spans LLM infrastructure and agents through bioinformatics, genomics, vision, and audio.

🟒 Open to senior / staff / lead AI & ML engineering roles (IC or founding) and AI-product roles β€” remote, or relocation for the right team. β†’ adoghri.com

πŸ’Ό Professional Work

Real systems shipped in regulated and B2B environments. Proprietary, not open source, but the discipline behind them is exactly what the repos below are built to demonstrate.

Project Description
LLM-Powered Regulatory Submission Automated FDA submission process using 7+ LLM pipelines, reducing errors by 60%.
AI-Driven RAG System NLP-powered retrieval-augmented generation system for pharmaceutical documents.
Streaming Data Platform Real-time event-driven ML pipeline on Kafka, Spark, and Flink.
Biomedical Text Enrichment Transformer models enriching research papers with biomedical insights.

🚒 Systems You Can Run End To End

These are not notebook demos. Each one has a usable interface, a backend or CLI, persistence where the product needs it, tests, CI, and a documented local or containerized run path.

Repo What ships Check it
spanjudge OTLP agent-trace receiver, SQLite store, operational dashboard, JSON API, CLI, Docker image, and regression policy gate Six spans rebuild three traces; the fixture passes latency, error, cost, and eval release limits
vrsbridge VCF parser, GA4GH VRS 1.3 translator, equivalence engine, browser workbench, JSON API, CLI, and Docker image Four VCF encodings collapse into two normalized molecular variants
leterminale Browser terminal, encrypted client-side workspace, import/export, keyboard workflow, and static deployment Open the live product and use it without an account or server-side document store

πŸ”¬ The Trust Layer

Ten local-first systems I wanted to exist: tools that decide what to trust across biology, agents, media, and audio. Each ships a CLI, JSON API, browser workbench, Docker image, tests, CI, and an explicit boundary around what its result does not prove.

Theme Repo What it checks Demo result
Spatial biology spatialniche Cell-type neighborhood enrichment against a permuted null Tumor neighborhood z = 5.10 across 250 permutations
Protein structure structuregrade Per-residue pLDDT bands and inter-residue geometry Grade C, mean pLDDT 71.88, two residues below 50
CRISPR genomics crisprradar Both-strand SpCas9 NGG mismatch and seed risk 1 exact + 2 off-target sites across 149 bases
Clinical genomics phenopacketlint GA4GH Phenopacket semantic exchange readiness Three phenotype assertions, quality score 100
Agent security mcpinterlock MCP tool authority, paths, approvals, secrets, and SSRF One call denied with 2 independent violations
ML privacy unlearnaudit Unlearning leakage against retained utility Membership AUC 1.000 β†’ 0.481, accuracy stays 0.988
Video privacy videoprivacy Tracked redaction through detector gaps 10 regions, two identities, one gap filled
Media provenance manifestlens C2PA ingredients, actions, signatures, and hard binding One ingredient, three actions, valid hard binding
Audio delivery loudnessgate EBU R128 loudness, range, peak, and normalization -18.4 LUFS, with a measured +2.4 dB correction
Music libraries audiocatalog Chromaprint duplicates across renamed or transcoded files One duplicate at 98.65% similarity

⚑ The Frontier Lab

Ten useful experiments at the edge of current ML engineering. Every result below comes from the committed fixture or an actual generated media artifact, not from the source paper.

Theme Repo End-to-end job Demo result
Genomics strandshift Audit sequence models across strand and window transforms 18 views, prediction range 0.7309
Rare disease phenorank Rank HPO disease candidates and test stability Top score 0.6334, stable 3/3
ML security tensorwarden Scan real checkpoint containers without loading them Safe artifact accepted; 2 quarantined
LLM privacy cacheisolate Reproduce and stop cross-tenant cache timing leakage 86 ms oracle removed with useful reuse retained
RAG security ragpoisonbench Inject corpus poison and test provenance quarantine Recall 1.0 β†’ 0.0 β†’ 1.0
3D vision splatgrade Parse and grade Gaussian Splat PLY artifacts Grade D / 49, every defect localized
Generated video physicsvideo Render MP4 scenarios and audit physical consistency 4/4 faults, 0 false positives
Multimodal media avsyncdoctor Detect and repair offset plus clock drift 120 ms, 5,000 ppm, repaired below 40 ms
Audio engineering codecguard Run real codec round trips behind a CI quality gate Clean build passes; degraded build fails 4/4 gates
Robot safety safepathshield Project policy actions onto a barrier constraint Collision steps 39 β†’ 0, goal still reached

πŸ† Flagship Open Source

Six focused repos that isolate the hard parts of shipping LLM systems: cost, safety, hallucinations, memory, evals, and injection defense.

Repo What it proves Result
vllm-cost-router Complexity-based routing, caching, and batching in front of vLLM 73% lower cost and p95 latency vs. always-large-model serving
guardrail-gate PII redaction + citation grounding + rate limiting in one pass 100% precision/recall on structured PII, 83% grounded-vs-hallucinated accuracy
semanticentropy Hallucination detection via semantic entropy (Farquhar et al., Nature 2024) Consistent answers score 0.08, hallucinations 0.90. No labels, no judge model
injectguard Prompt injection and jailbreak detection with explainable verdicts 100% precision and recall on a red-team corpus of attacks and lookalikes
agentmem Bounded, self-consolidating long-term memory for LLM agents Salience-gated writes, decay-aware retrieval, a hard budget it actually respects
citebench What reranking actually buys you in citation-grounded RAG Citation precision 62% β†’ 88% on an adversarial benchmark

🧬 Five Research Themes, Ten Working Reproductions

Current research reduced to one mechanism, one baseline, and one number you can rerun. Every repo is MIT licensed, standard-library Python, and tested on 3.9, 3.11, and 3.13.

Theme Repo What it proves Reproduced result
Bioinformatics cellcontext Cellular context matters for perturbation response MAE 0.2699 β†’ 0.1813
Bioinformatics foldcontact Contact constraints keep protein infilling fold-aware Satisfaction 34.5% β†’ 100%
Genomics pangraphmap Pangenome paths recover structural-variant reads a linear reference loses 6/25 β†’ 25/25 mapped
Genomics methyloadapt Conserved motifs transfer when target-species labels run out Accuracy 50% β†’ 100%
Machine learning driftfilter Forward-only prototypes follow gradual deployment drift Accuracy 77.9% β†’ 100%
Machine learning taskrouter Routing preserves specialists that static merging averages away MAE 1.379 β†’ 0.000
Vision + video distractrack Motion and identity memory prevent swaps at object crossings Accuracy 73.8% β†’ 100%
Vision + video d3video Synthetic motion artifacts show up in the difference of differences Accuracy 50% β†’ 100%
Sound + music restem A separator can improve itself over multiple inference steps SNR 8.78 β†’ 36.52 dB
Sound + music binauralbench A clean stem still fails if it collapses the spatial cue ILD error reduced 98.3%

πŸ§ͺ The Rest of the Lab

The same standard (reproducible benchmark, tests, CI, zero dependencies) applied across the stack. Grouped so you can jump to what you care about.

LLM inference and cost. speculabench (speculative decoding math, 1.4x to 2.9x), kvsqueeze (KV-cache eviction, H2O and StreamingLLM style), contextpack (prompt compression with a recall check).

Output reliability. structstream (JSON repair, 7% β†’ 100% recovery), rubricagent (LLM-as-judge rubrics learned from outcomes, AUC 0.77 β†’ 1.00), taggate (confidence-gated tagging in TypeScript).

RAG done honestly. chunklab (chunking strategies, measured), clarifyrag (asks clarifying questions only when evidence disagrees), tablextract (tables out of PDFs with cited cells).

Agents that stop. toolrouter (tool selection that abstains on ties), agentbudget (loop detection catching stalls that step limits miss), debatekit (multiagent debate, 57% β†’ 80%).

ML beyond LLMs. churnfm (drift-triggered retraining), orthoshift (double ML for causal effects), fedcal (non-IID federated learning), riskbandit (conformal risk-controlled bandits), chronopatch (conformal forecasting), graphpulse (graph anomaly scoring), tabflowmini (synthetic tabular data with an audit), proteinmask (masked protein-like infilling, honestly toy), pendulumlab (CEM control from scratch), motifdiff (symbolic music that grades itself), connectpuct (PUCT Connect Four you can play).

πŸ› οΈ Products People Actually Use

Tool What it does
leterminale A private, keyboard-first writing terminal with encrypted local workspaces and no account requirement.
VectorMorph SVG to animated WebP/GIF with frame blending. Built because Figma's export flaked one time too many.
ATSProofResume Tailors your resume to a job posting without inventing experience. The free version of a $29/month industry.
bookconverter Local EPUB/MOBI/PDF conversion. No upload limits, no queues, no well-hidden subscription.

πŸ“¬ Get in Touch

Website LinkedIn

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  1. agentmem agentmem Public

    Most agent memory is a junk drawer with embeddings. This one has opinions: salience-gated writes, decay-aware retrieval, and a hard budget it actually respects.

    Python

  2. clarifyrag clarifyrag Public

    Most RAG agents answer confidently about the wrong thing. This one asks first, but only when the evidence actually disagrees. 100% accuracy, 38% fewer questions.

    Python

  3. rubricagent rubricagent Public

    You wrote your eval rubric once and never checked if it predicts anything. This learns the real one from outcomes. AUC climbs 0.77 to 1.00, zero API keys.

    Python

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