Pre-screened and vetted.
Staff Applied Scientist specializing in multimodal LLM safety, robustness, and retrieval
“Built a production LLM-driven archival assistant that turns large, low-quality scanned handwritten files (120+ pages) into structured datasets, overcoming context-window and hierarchy challenges with a two-phase LLM + rules pipeline and reaching 98.1% accuracy (Gemini-2.5 Flash). Also orchestrated a large human-in-the-loop effort with 78 archivists, producing 2,400 high-quality annotations in 4 days via detailed rubrics and support.”
Executive Talent Acquisition Leader specializing in Financial Services and Technology
“Global talent acquisition leader and player-coach with 15+ years managing recruiter teams (up to 25–30) across multiple regions. Has personally delivered executive searches (including CIO and engineering leadership) and driven enterprise-wide recruiting improvements, including building a global structured interview/assessment program at NASDAQ. Partnered directly with CEO/CFO/CHRO to shift compensation strategy during a high-attrition period (50%) to stabilize hiring and retention.”
Mid-level AI/ML Engineer specializing in LLMs, FinTech, and Healthcare IT
“Built production GenAI systems in both healthcare and financial services, including a Verily clinical platform and an Accenture financial Q&A product. Stands out for combining advanced RAG, fine-tuning, safety evaluation, and infrastructure engineering to deliver measurable gains in engagement, groundedness, hallucination reduction, and cost efficiency.”
Mid-level Software Engineer specializing in AI/ML and full-stack systems
“Engineer with Apple experience building LLM-powered internal workflow orchestration systems using Python, LangGraph, FastAPI, Redis, vector search, and Kubernetes. Stands out for a highly pragmatic, production-focused approach to agentic systems: deterministic state management, strong guardrails, observability, and human review for high-risk actions.”
“Machine learning software engineer intern experience at Amazon, where they built a production testing framework to inject frames/videos onto devices to measure embedded CV model inference and ensure broad model compatibility via automatic NNA metadata handling. Also built side projects spanning LLM/RAG orchestration (LangChain/LangGraph with reranking and citations) and applied CV/healthcare work (nail disease detection, medical retrieval chatbot).”
Mid-level Machine Learning Engineer specializing in GPU-accelerated LLM training and inference
“ML/LLM engineer with production experience building a multi-GPU LLM inference platform using TensorRT and vLLM, achieving ~40% p95 latency reduction through batching/KV caching, quantization, and CUDA/runtime tuning. Also has end-to-end orchestration experience (Kubernetes, Airflow) and has delivered real-time fraud detection systems at Accenture in close collaboration with non-technical risk and product stakeholders.”
Executive Technology Leader (CTO) specializing in AI-enabled SaaS and regulated platforms
“Senior engineering leader with experience at Disney and BlackLine who drives business-aligned technology roadmaps through deep Product/Engineering partnership (two-in-a-box) and pragmatic prioritization frameworks. Has led major modernization initiatives—private-to-public cloud migration to GCP with multi-cloud evolution, data-layer performance improvements (Mongo/Redis, caching/query optimization), and tooling upgrades (VSS to GitHub)—while scaling teams with strong quality and accountability culture.”
Mid-level Data Science AI/ML Engineer specializing in Generative AI, LLMs, and RAG systems
“Built a production RAG-based "knowledge copilot" for support/ops using LangChain/LangGraph, implementing the full pipeline (ingestion, chunking, embeddings, vector DB retrieval/rerank, guarded generation with citations) and operating it as monitored microservices with CI/CD. Also designed an event-driven, streaming backend for real-time inventory ordering predictions that reduced stockouts by 25%, and has hands-on incident response experience stabilizing LLM API latency/5xx spikes using Datadog/APM and resilience patterns.”
Junior Software Engineer specializing in AI/ML systems and LLM-powered document automation
Mid-level AI Engineer specializing in computer vision and RAG systems
Junior Machine Learning Engineer specializing in LLMs and retrieval-augmented generation
Intern AI/ML Engineer specializing in LLM systems and cloud-native microservices
Senior AI/ML Software Engineer specializing in LLM and RAG systems
Senior Full-Stack Engineer specializing in AI, cloud microservices, and blockchain
Senior Engineering Manager specializing in observability platforms and Generative AI
Junior Software Engineer specializing in healthcare data and LLM-powered workflows
Intern Perception/Robotics Engineer specializing in computer vision and embodied AI
Senior Full-Stack Software Engineer specializing in AI, cloud platforms, and SaaS
Mid-level NLP Research Engineer specializing in LLM evaluation and retrieval-augmented QA
Mid-level Python Full-Stack Developer specializing in FinTech and ML systems
Senior AI/ML Engineer specializing in Generative AI, NLP, and LLM systems
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and GPU-accelerated deep learning