Pre-screened and vetted.
Mid-level Data Scientist / AI/ML Engineer specializing in Generative AI and healthcare analytics
Senior Full-Stack Engineer specializing in Unity, multiplayer networking, and VR/mobile
Director-level Agile and IT leader specializing in enterprise automation and logistics
Director-level sales leader specializing in OEM, aftermarket, and industrial equipment markets
“Public-sector sales leader in emergency vehicle and municipal fleet equipment who drove $90M in combined incremental growth across SoundOff Signal and Buyers Products. Stands out for winning entrenched government accounts through product-led displacement strategies, disciplined KPI/CRM management, and persistence in long-cycle agency sales, including converting Houston PD from a longtime competitor.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
“Backend engineer with experience in both healthcare (Siemens) and payments (Bitwise), focused on scaling Python APIs and modernizing architectures. Has led monolith-to-microservices migrations and introduced Kafka async processing, Redis caching, and ELK observability, citing ~40% faster issue resolution and improved reliability via idempotency and strong security controls (OAuth2/JWT, RBAC, RLS).”
Senior Machine Learning Engineer specializing in NLP, computer vision, and edge AI
“AI/LLM engineer who built a production RAG-based Text2SQL engine using Qdrant, including creating the underlying business/DB documentation, generating a test dataset, and designing detailed SQL-quality metrics for validation. Also partnered with non-technical stakeholders on a speech recognition project to prioritize medical terminology, improving accuracy through targeted corpora, lookup-table correction, and fine-tuning with a modified loss function.”
Mid-level AI/ML Engineer specializing in fraud detection, recommender systems, and forecasting
“ML engineer/data scientist who built and deployed a real-time fraud detection platform at Citi on AWS SageMaker, processing 3M+ daily transactions and improving fraud response by 28%. Combines unsupervised anomaly detection (autoencoders) with ensemble models (XGBoost/Random Forest) plus Airflow/Step Functions orchestration, drift monitoring, and explainability (SHAP) to keep models reliable and compliant in production.”
Mid-level Full-Stack Developer specializing in healthcare cloud applications
“Master’s-program backend engineer with strong Java/Spring Boot industry experience who also owned a Python analytics service (Flask/Postgres, JWT, Celery/Redis) and optimized large-dataset performance via SQL/batching. Has hands-on Kubernetes microservices deployment and GitLab+Terraform CI/CD/GitOps workflows, plus experience supporting phased on-prem to AWS migrations and building Kafka-based real-time streaming pipelines.”
Mid-level Full-Stack Developer specializing in Python/Java and cloud-native web apps
“Robotics-focused full-stack engineer with hands-on ROS experience building sensor-processing and control nodes, plus a track record of debugging and optimizing real-time robot responsiveness via profiling and message-timing analysis. Uses Webots for pre-hardware validation and Docker/CI/CD to standardize deployments and catch issues early.”
Mid-level Software Engineer specializing in Java microservices and ML model integration
“Backend/ML platform engineer who owns end-to-end delivery of ML-serving APIs (FastAPI + TensorFlow) and runs them reliably on Kubernetes using ArgoCD GitOps. Has hands-on experience solving production-only issues (probe tuning for model warm-up, resource profiling) and building scalable Kafka streaming pipelines, plus supporting phased on-prem to AWS migrations with dependency discovery and recreation of hidden jobs/workflows.”
Mid-level Data Scientist specializing in cloud ML, MLOps, and predictive analytics
“NLP/ML engineer with hands-on healthcare and support-ticket text experience, building clinical-note structuring and semantic linking systems using spaCy, BERT clinical embeddings, and FAISS. Emphasizes production-grade delivery (Airflow/Databricks, PySpark, Docker, AWS/FastAPI/Lambda) and rigorous validation via clinician-labeled datasets, retrieval metrics, and user feedback.”
Junior Software Developer specializing in AI/LLM agent systems
“Built an LLM-powered agent within the Nora AI analytics platform to automate e-commerce product performance analysis and generate actionable recommendations (pricing/inventory), designed with production-grade reliability patterns and observability. Emphasizes predictable, schema-validated tool/function-calling pipelines with robust fallbacks, idempotency, and guardrails for messy operational data.”
Mid-level Full-Stack Developer specializing in AI automation and RAG pipelines
“Frontend engineer who has led mobile-first and web React/TypeScript products end-to-end, including an expense tracking app handling sensitive financial data and a real-time messaging/activity dashboard with chat, presence, and contextual side panels. Emphasizes scalable architecture, rigorous component-boundary testing, and production-safe rollout practices (feature flags, analytics/logging, staged releases) to ship reliably in fast-paced environments.”
Director-level Women’s Basketball Coach specializing in recruiting and player development
“Former college basketball coach and 12-year Division I recruiting coordinator who recently left Regis University to found Level Up Coaching, providing individual player development and recruiting guidance. Deeply connected in the Colorado club/high school ecosystem and experienced recruiting nationally, with strong on-camera and social content capabilities (including current skill-video work with Gold Crown Foundation and D1 analyst work at University of Wyoming).”
Executive product leader specializing in FinTech, SaaS, and digital transformation
“Product leader with experience spanning telecom, fintech mortgage, and hospitality, including a major AT&T rebuild of a fragmented digital sales flow and AI-enabled lending/onboarding products. Brings a strong mix of legacy modernization, cross-functional alignment, UX iteration, and human-centered thinking about AI as an amplifier rather than a replacement.”
Mid-level Full-Stack & AI Engineer specializing in LLM-integrated cloud applications
“Built an AI immigration compliance co-pilot for F1 OPT and STEM OPT students, combining rule-based risk assessment with LLM-powered guidance on a React/TypeScript and AWS serverless stack. Stands out for thoughtful handling of high-risk AI: grounding responses in structured compliance data, adding guardrails, and keeping legal interpretation human-in-the-loop. Also contributed to an education-focused AI product for teachers and helped expand it with quiz generation and document editing features.”
Senior 3D Generalist specializing in real-time 3D, VR, and procedural animation
“UK-based Unity/VR generalist who shipped a Meta Quest VR installation to art galleries worldwide while at Julian Opie Studio, acting as sole programmer and producing the art pipeline. Built a custom Spatial Anchors-based spatial mapping system with little documentation and developed real-world operational procedures to keep installations stable for exhibitions with hundreds of daily visitors. Also contracted as a 3D generalist at Blue Zoo, producing all assets/animations and environment setup for a Tate Gallery kids game, finishing ahead of schedule.”
Senior Business Operations & Supply Chain Manager specializing in IoT SaaS and hardware GTM
“Cross-functional operator at Andium who led founder-level initiatives spanning next-gen product launch + legacy sunset, built decision-driven operating cadences (dashboards, memos, blocker tracking), and drove international expansion after a Series B led by Saudi Aramco. Also supported a $6M strategic opportunity in Australia by coordinating pricing, product feedback loops, and internal alignment across an AI-enabled SaaS + hardware business.”
Mid-level DevOps Engineer specializing in cloud automation and DevSecOps
“Cloud/hybrid infrastructure engineer with McKesson experience migrating tightly coupled healthcare applications to microservices on AWS EKS. Strong in IaC-driven standardization, CI/CD automation, and production observability (CloudWatch/Splunk/Prometheus/tracing), with demonstrated ability to debug complex incidents spanning Kubernetes and cloud networking.”
Principal Data Scientist specializing in cybersecurity ML and MLOps
“ML/NLP engineer (Beyond Identity) who built production semantic search and entity-resolution systems over internal security documentation, using LDA + BERT embeddings with FAISS/Pinecone to cut search time by 30%. Also scaled a real-time anomaly detection pipeline to millions of events/day with Spark and AWS Lambda, with strong emphasis on measurable validation (Precision@k, MRR, F1, ARI).”
Mid-level Technical Support Engineer specializing in backend troubleshooting and SQL/API diagnostics
“TSE with hands-on experience troubleshooting customer-reported data issues across APIs and SQL, coordinating with engineering on hotfixes, and translating risk to non-technical stakeholders. Has supported application security workflows using Veracode by generating reports, driving remediation via Jira, and tracking exposure metrics; also assisted customers with SSO setup (client ID/secret).”
Junior Full-Stack Software Engineer specializing in React, Kubernetes, and AI-powered apps
“Backend/DevOps-leaning engineer managing multiple customer service platforms end-to-end (requirements through deployment). Built an in-house Python monitoring/alerting solution for Salesforce-to-Java contact sync jobs (Snowflake dependencies) that increased uptime ~60%, and helped modernize delivery by moving the team from manual releases to automated Jenkins-based deployments while coordinating an Oracle EBS→Fusion transition with business/data/IT stakeholders.”
Mid-level AI/ML Engineer specializing in MLOps, NLP, and scalable model deployment
“Built and deployed a production autonomous AI data analyst agent (LangChain + GPT + Streamlit on AWS) that turns natural-language questions into validated SQL, visualizations, and insights, cutting manual analysis time by ~50%. Emphasizes reliability and MLOps: schema-aware validation/guardrails to prevent hallucinations, scalable large-data processing, and Azure DevOps CI/CD + MLflow for automated deployment and experiment tracking.”