Pre-screened and vetted.
Director-level Product and Data Executive specializing in B2B SaaS and analytics
“Product leader with a strong track record of modernizing legacy SaaS platforms, including an API-first rebuild that increased engagement by 40% and reduced support burden. Also led AI-powered workflow automation that delivered 80-90% time savings through human-in-the-loop design, showing a pragmatic, user-centered approach to applied AI.”
Mid-level Supply Chain Planner/Buyer specializing in sourcing, MRP, and analytics
“Supply chain/sourcing professional focused on semiconductor tooling NPI ramp-ups, owning vendor selection through production and delivery. Demonstrates strong cost and trade-risk mitigation (e.g., avoided 25% Section 301 tariff via HTS/landed-cost analysis) and measurable supplier performance turnarounds (OTD improved to 95%) using SAP MRP, shortage analysis, and structured supplier governance.”
Junior Software Engineer specializing in AI/ML and verification
“Embedded/real-time robotics-style engineer with hands-on STM32 development, sensor integration, and low-level drivers, focused on deterministic control behavior. Demonstrated systematic debugging of jitter/latency by instrumenting the sensing-to-actuation pipeline and eliminating blocking via interrupts, hardware timers, and DMA; also designs asynchronous, message-based interfaces for distributed real-time components. Familiar with ROS/ROS2 concepts (nodes/topics/callbacks) though not yet deployed a full production ROS system.”
Mid-Level Software Engineer specializing in microservices and cloud data pipelines
“Full-stack engineer with end-to-end ownership across React/TypeScript frontends, Spring Boot/Node microservices, and production ops on Docker/Kubernetes and AWS (ECS/CloudWatch). Built real-time healthcare eligibility and analytics systems at Cigna and an early-stage seller onboarding platform at Flipkart, driving measurable performance gains (35–40% latency/throughput improvements) through event-driven Kafka pipelines, Redis caching, and strong reliability/observability practices.”
Junior Software Engineer specializing in full-stack, cloud serverless, and AI systems
“SDE who worked on an MGICS Lab robotics project building a multi-agent model to help agents understand tasks and generate robot instructions, emphasizing task-splitting, checking, and a reflection agent to improve accuracy. Also has experience using GitHub with automated CI/CD pipelines.”
Mid-level Growth Marketing Manager specializing in performance creative and marketing analytics
“Paid social creative lead with experience across major consumer brands (Duracell, Amazon Groceries, Puma) and Gen Z-focused retail, owning end-to-end creative strategy from concept/briefing and UGC direction through QA and delivery. Known for contextual, seasonally-timed campaigns and performance-driven iteration (CPA/ROAS, funnel drop-offs), including a Duracell Meta campaign that reached 20M+ views and sustained engagement gains via creator feedback loops.”
Principal Data Strategy & Data Management Leader specializing in enterprise governance and analytics
“Operator/program leader with experience building operating models and execution cadences for data/analytics and energy data services across Entech, HealthEquity, and RealPage. Has launched an undefined energy data management service into regulated enterprise environments and driven cross-functional alignment via dashboards, SLAs, and OKRs—contributing to enterprise wins and a successful company sale.”
Mid-level Data Analyst specializing in machine learning, ETL, and real-world evidence analytics
“Developed and productionized an AI-driven "indication finding" system for AbbVie to identify additional diseases a drug could target, working closely with clinical research teams on cohort inclusion/exclusion criteria and disease rollups. Leveraged an LLM to map clinical inputs to ICD codes and built configuration-driven ML pipelines (Cloudera ML, YAML, scheduled jobs) with structured testing and evaluation for reliability.”
Mid-Level AI/ML Software Engineer specializing in agentic LLM systems
“Built and deployed a production LLM-powered multi-agent compliance copilot (life sciences/finance) using LangChain/LangGraph + RAG over vector databases, delivered via async FastAPI on Kubernetes. Emphasizes audit-ready, deterministic outputs with schema constraints and citations, plus rigorous evaluation/monitoring; reports 60%+ reduction in manual research time and successful production adoption.”
Junior Machine Learning Engineer specializing in MLOps and LLM/RAG systems
“LLM/agentic workflow builder focused on productionizing document-processing systems. Redesigned pipelines with LangGraph + RAG, schema-aware validation, and eval/monitoring loops; known for fast incident diagnosis (restored accuracy from ~70% to >95% same day). Partners closely with sales and stakeholders to deliver tailored demos and drive adoption (reported +40%).”
Mid-level Marketing & Sales Development Associate specializing in public sector SaaS/EdTech
“Public-sector-focused consultant with hands-on ownership of outbound/ABM, lead gen, and GTM strategy for early-stage and pre-launch products (including edtech). Built multi-channel campaigns spanning SEO/web copy, email, conferences, and direct outreach to state/district leaders, and created an Airtable onboarding system that cut prospect research time by 33%.”
“LLM/agent workflow engineer with healthcare experience (CVS/CBS Health) who built and deployed a production call-insights platform using Azure OpenAI + LangChain/LangGraph, including sentiment and compliance checks. Demonstrates deep HIPAA/PHI handling (tenant-contained processing, redaction, RBAC/encryption/audit logging) and production rigor (testing, eval sets, validation/retries, autoscaling) to scale to thousands of transcripts.”
“Built and deployed a production Retrieval-Augmented Generation (RAG) platform in a healthcare setting to automate clinical documentation review and summarization, targeting near-real-time, explainable outputs. Emphasizes grounded generation to reduce hallucinations, latency optimizations (chunking/embedding reuse), and PHI-safe workflows with access controls, plus strong orchestration experience using Apache Airflow.”
Executive HR & Talent Consultant specializing in culture, DEI, and hiring science
“Org/people advisor with 20+ years applying systems thinking and data-driven methods to high-stakes change—spanning DEI transformations at an international consulting firm, profitability turnarounds in eldercare via company-wide facilitation, and executive coaching. Also designs compensation benchmarks for novel roles at international tech companies, enabling successful global hiring and growth.”
Mid-level Data Scientist / AI-ML Engineer specializing in Generative AI and LLM applications
“Built a production GenAI-powered analytics assistant to reduce reliance on data analysts by enabling natural-language Q&A over Databricks/Power BI dashboards, backed by vector search (Pinecone/Milvus) and a Neo4j knowledge graph, including multimodal support via OpenAI Vision. Demonstrates strong real-world LLM reliability engineering with strict RAG, LangGraph multi-step verification, and Guardrails/custom validators, plus broad orchestration and production monitoring experience (Airflow, ADF, Step Functions, Kubernetes, Prometheus/CloudWatch).”
Mid-level Supply Chain Analyst specializing in logistics optimization and planning analytics
“Supply chain/procurement professional (Maersk) who leads end-to-end freight sourcing initiatives using heavy analytics (SAP/SQL/Python/Excel) to drive measurable savings. Known for automating sourcing workflows (60% faster bid evaluation) and building Power BI dashboards to monitor contract compliance and supplier performance post-implementation.”
Director-level AI & Data Science leader specializing in GenAI, LLMs, and MLOps
“ML/NLP engineer currently working in NYC on a system that connects complex unstructured data sources to deliver personalized insights, using embeddings + vector DB retrieval and a RAG architecture (LangChain, Pinecone/OpenSearch). Strong focus on production constraints—especially low-latency retrieval—using FAISS/ANN, PCA, index partitioning, and Redis caching, plus PEFT fine-tuning (LoRA/QLoRA) and KPI/SLA-driven promotion to production.”
Staff Full-Stack Engineer specializing in AI platforms and infrastructure automation
“Backend/full-stack engineer building complex internal platforms and customer-facing demos at the intersection of infrastructure and product. Shipped a no-code Product Lifecycle Manager for manufacturing (3 manufacturers, 1000+ evolving tests) using AWS S3/SQS ingestion and extensible Postgres (EAV+JSONB) with end-to-end traceability. Also built a FastAPI-based company data intelligence platform with Okta-secured RBAC and an LLM/MCP layer for ChatGPT-like analytics over enterprise data sources.”
Mid-level AI/ML Engineer specializing in deep learning, NLP/LLMs, and MLOps
“Built and shipped a real-time oncology risk prediction system used by doctors during patient visits, trained on clinical data in AWS SageMaker and deployed via FastAPI with sub-second responses. Emphasizes clinician-trust features (SHAP explainability, validation checks) and HIPAA-compliant controls (encryption, RBAC, audit logging), plus Kubernetes-based production operations with autoscaling, monitoring, and drift/retraining workflows; collaborated closely with oncologists at Flatiron Health.”
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
“Software engineer with strong compliance-domain experience who built a customer-facing compliance and reporting dashboard using React/TypeScript with Spring Boot microservices. Demonstrates mature production engineering practices—contract-first APIs, event-driven architecture (Kafka/RabbitMQ), caching (Redis), and robust CI/CD + observability (Prometheus/Grafana/ELK)—and also created a Python-based audit automation tool adopted into the standard release process.”
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and Conversational AI
“Built a production RAG-based GenAI copilot backend at Aetna using Python/FastAPI, GPT-4, LangChain, and Azure AI Search, deployed on AKS with Prometheus/Grafana observability. Owned the system end-to-end (ingestion through deployment) and improved peak-time reliability by addressing vector search and embedding bottlenecks with Redis caching, index optimization, and async processing, plus added anti-hallucination guardrails via retrieval confidence thresholds.”
“字节跳动实习期间将内部AI重量预测模型从“可用但难上线”的单点能力,改造成可商业化复用的通用API:统一多地区接口与评估口径,设计分层兜底与置信度分级,先灰度上线SEA/JP并推动US/EU落地,结合线上结果进行模型微调。具备LLM/RAG/Agent系统的实战排障方法论,以及面向开发者与售前场景的技术演示与跨团队推进能力。”
Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps on AWS
“AI engineer who built a production RAG-based internal analyst tool at BlackRock, fine-tuning an LLM on proprietary financial data and adding four layers of guardrails (input/retrieval/generation/output) to improve grounding and reduce hallucinations. Implemented a LangChain-based multi-agent orchestration (7 major agents) deployed on AWS ECS, with reliability measured via internal human evaluation, LLM-as-judge, and RLHF/drift monitoring.”
Mid-level Supply Chain Analyst specializing in planning, procurement, and distribution operations
“Sourcing/procurement professional with Accenture experience supporting telecom infrastructure expansion, owning RFQs through delivery and managing 12+ vendors. Known for strong supplier performance management (scorecards, KPIs, corrective actions) delivering ~97% on-time material delivery while cutting expedited freight 13% and avoiding ~AUD 500K in delay costs; also brings supplier onboarding and capability/capacity assessment experience from Nestlé and Accenture.”