Pre-screened and vetted.
Senior Full-Stack Engineer specializing in cloud-native microservices and AI/LLM integrations
Executive Product Development & Operations leader in life sciences and diagnostics
Mid-level Strategy & Data/AI Consultant specializing in retail, supply chain, and transformation
Junior Full-Stack Software Engineer specializing in React, APIs, and Industrial IoT data platforms
Executive AI/ML & HPC Architect specializing in enterprise and multi-cloud transformation
Senior Full-Stack Software Engineer specializing in AWS cloud-native microservices and healthcare platforms
Director of Enterprise Analytics specializing in AI/ML for healthcare and insurance
Mid-level Agentic AI & ML Engineer specializing in LLM agents and RAG systems
Mid-Level Software Engineer specializing in cloud-native backend and distributed systems
Staff Product Manager specializing in FinTech and enterprise SaaS platforms
Director of Talent Acquisition specializing in workforce planning, analytics, and internal mobility
“Operations and talent strategy leader who has supported two early-stage tech startups by optimizing org structure and building scalable recruiting operations. Implements KPI-driven hiring systems, employer branding/attraction strategies, and DEI/SMART/SWOT frameworks, and has a concrete example of reducing declined offers by shifting compensation discussions earlier and training hiring managers. Experienced mentoring founders/executives through mission-aligned, flexible development plans and structured communication processes.”
“Software engineer with experience at Amazon and Agora building end-to-end systems: a knowledge-base AI chatbot (React/TypeScript UI + retrieval/response backend + Docker deployment) and an internal approval governance platform using AWS Step Functions and DynamoDB. Emphasizes fast iteration without sacrificing trust via feature-flag rollouts, citation-required answers, abstention on low-confidence retrieval, regression query sets, and strong observability (request IDs, structured logs, latency/error monitoring).”
Mid-level Machine Learning Engineer specializing in LLMs, fairness, and healthcare ML
“ML/NLP practitioner with a master’s thesis focused on domain-adaptive knowledge distillation for LLMs (LLaMA2/sheared LLaMA), showing improved perplexity and ROUGE-L on biomedical data. Also built real-world data linking and search systems: integrated ClinicalTrials.gov with FAERS using fuzzy matching + embeddings, and delivered an LLM-powered FAQ recommender at Hyperledger using sentence-transformers, FAISS, and fine-tuning to mitigate embedding drift.”
Mid-level Software Engineer specializing in backend systems, IoT, and AI security
“Full-stack engineer in the investment tracking/financial reporting space who built an automated reporting dashboard and compliance/reporting pipeline end-to-end using Next.js (App Router, server/client components), REST, and Postgres. Demonstrated measurable performance wins (~30% faster loads) through caching and query optimization, and built durable orchestrated workflows in n8n with retries, idempotency, and reconciliation checks.”
Senior Data Engineer & Render Tools Developer specializing in VFX and render farm pipelines
“Real-time simulation/physics engineer who optimized character effects and cloth for the "Infinity" game by implementing and profiling multiple ODE integrators, including pioneering the largely undocumented Parker-Sochacki method (optimized 5/7 sims; >30% speedup on a particle system). Also built SPH fluid solvers in Unity (C#) and created Grafana/Python Dash dashboards to analyze latency/throughput, with strong interest in applying math/physics and tooling to soccer/football gameplay.”
Senior Software Engineer specializing in distributed systems and AI workflow orchestration
“Backend owner at Apple for an AI workflow orchestration service, with hands-on experience stabilizing peak-traffic production systems using OpenTelemetry-style tracing, bounded async concurrency, and database performance tuning. Built and shipped a Python LLM-agent orchestration layer to automate multi-step operational workflows, emphasizing guardrails, auditability, and deterministic fallbacks to keep non-deterministic AI behavior production-safe.”
Mid-level AI/ML Engineer specializing in MLOps, LLMs, and scalable ML systems
“ML/LLM engineer at Adobe who deployed a transformer-based personalization and campaign-targeting recommender system end-to-end, including PySpark/Airflow pipelines processing 12M+ events/day and containerized inference on AWS SageMaker (Docker/Kubernetes). Also has hands-on LLM workflow experience (RAG, semantic search, prompt optimization, hallucination mitigation) with a metrics-driven approach to reliability, drift monitoring, and reproducible retraining via MLflow.”
Executive Operations & Supply Chain Leader specializing in multi-site fulfillment networks
“Operations leader with Amazon experience owning a founder-level initiative during national supply chain Regionalization, building and scaling a "Stack-to-Light" operating mechanism to standardize non-sortable FC execution with instrumentation and balanced-scorecard metrics. Later joined Revivn to stabilize an underperforming operation by developing frontline leaders and aligning ops with finance and GTM through clear KPIs and operating cadence.”
Director-level Strategy & Operations leader specializing in GTM, product, and operating cadence systems
“Operator/strategy leader with experience driving digital transformation and building executive operating systems in high-noise environments. At a legacy B2C brand, created a prioritization framework and exec alignment process that cut 100+ initiatives to 16 and lifted execution from 12% to 81%. At Point B, owned a $20M delivery budget while shifting the firm to a tech-forward practice, implementing OKR/KPI cadences and AI-enabled workflows (n8n, LLMs, gamma.ai) that materially improved executive productivity.”
Senior Technical Designer specializing in gameplay systems and Unreal Engine
“Player Experience developer on Madden who shipped player-facing Weekly Recap and Halftime Show flows built in visual scripting, including a custom solution to keep full-screen UI persistent across level loads with strong logging and failsafes. Also builds networked UE co-op ARPG systems (talent trees, combat/animation, leveling/stats, AI, dynamic spawning) and has a track record of refactoring shared UI/banner logic into scalable prefabs to reduce bugs and improve team workflow.”
Mid-Level Backend Engineer specializing in SaaS automation and data platforms