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Wassim Bannout — Machine Learning Engineer
Machine learning engineer in Beirut. I build ML and LLM systems with the evaluation harness attached — measured retrieval, calibrated probabilities, reproduc...
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81 % |
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Joseph Stickel - AI Systems Engineer
AI systems engineer who designs and ships production AI end to end - RAG pipelines, agentic assistants, measured retrieval quality, and multi-provider LLM in...
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80 % |
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EVALution — AI evaluation for teams shipping LLM features
EVALution helps companies integrating AI measure whether it actually works: evaluation frameworks, pre-launch readiness audits, and regression evals that run...
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80 % |
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Antagon Inc. | Evidence about what AI systems actually do
Antagon Inc. builds instruments that produce checkable evidence about AI systems. Veteran-owned small business, non-traditional defense contractor. UEI KBSGT...
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80 % |
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Rohit Agrawal — AI systems that show their work
Independent, inspectable AI systems built on citation, disclosed uncertainty, honest refusal, and release gates — by a principal-level engineer with 14+ year...
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80 % |
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Kenneth W. Bingham · AI Engineer: RAG, Pipelines, Evaluation
AI engineer building retrieval systems that cite their sources, ingestion pipelines that are safe to re-run, and evaluation harnesses that measure hallucinat...
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79 % |
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Kenneth W. Bingham · AI Engineer: RAG, Pipelines, Evaluation
AI engineer building retrieval systems that cite their sources, ingestion pipelines that are safe to re-run, and evaluation harnesses that measure hallucinat...
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79 % |
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CodeEvolver — We build self-improving AI systems
CodeEvolver is an AI engineer in an experimentation loop: it proposes changes to your prompts and code, tests every change against your data, and keeps only...
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79 % |
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mairunner — the judgment layer for autonomous engineering
mairunner governs coding agents at scale — task contracts, mechanical enforcement, and verification tiers that let autonomy be earned instead of assumed. Bet...
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79 % |
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Rushil Jaiswal
Rushil Jaiswal. I build AI systems that have to be right, and I audit the things that decide whether they are.
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79 % |
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jeval — Know when your AI gets it wrong.
Open-source evaluations for AI outputs and agents. Define your checks, run them with Jev, and inspect failures and uncertain results.
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79 % |
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Alex Morgan — AI Product Engineer
AI Product Engineer building evaluated LLM, RAG, agentic AI, and production ML systems. Explore selected case studies and engineering outcomes.
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79 % |
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Jason Stiltner: Staff AI Engineer | Agent Evaluation & Evaluator Reliability
I build systems for knowing whether production AI actually works: the evals that catch failures, the tooling that explains them, and tests of whether the eva...
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78 % |
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Evaluate AI without the sales pitch. | NeutralIntelligence
Define the use case, document the evidence and compare systems against the requirements that actually matter.
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78 % |
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Dan Krawczun
Agentic AI workflows for enterprise teams, built end-to-end: process mapping, requirements, tooling, regression-tested implementation, and adoption support....
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78 % |
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Devin Jackson — AI systems that hold up in production
Senior AI engineer. I take AI features that are already live and failing in ways the prototype never did, and make them reliable, observable, and affordable...
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78 % |
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Andrew Bottoni — Principal engineer for consequential systems
Andrew Bottoni takes ownership of difficult software systems—legacy rescue, integration, data integrity, financial platforms, and AI-assisted delivery—when f...
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78 % |
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Erised Labs - Reliable RL Scaling
Erised Labs works on reliable environment construction and reward modeling, data auditing and selection, and the training infrastructure behind agentic reinf...
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78 % |
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Ares Intelligent Systems
Ares Intelligent Systems builds scientific systems that mark the parts of an answer they cannot support.
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78 % |
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devx-ai — LLM Evaluation & Observability
Evaluate, trace, and test your LLM applications.
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78 % |
Detected social media networks