Pre-screened and vetted.
Intern Product Manager & Software Engineer specializing in data analytics and AI
Senior Mechanical/Systems Engineer specializing in automation, additive manufacturing, and defense
Mid-Level Software Engineer specializing in backend services and full-stack web apps
Intern Perception/Robotics Engineer specializing in computer vision and embodied AI
Junior Software Engineer specializing in healthcare data and LLM-powered workflows
Senior Full-Stack Engineer specializing in FinTech and e-commerce platforms
Intern Software Engineer specializing in cloud infrastructure and machine learning
Intern Data Scientist specializing in LLMs, RAG, and data engineering
Staff Full-Stack & AI Engineer specializing in LLM agents, RAG, and cloud-native systems
Engineering Manager specializing in AI/ML and full-stack product delivery
Technology Executive specializing in AI-native engineering and cybersecurity governance
Junior Robotics & AI Engineer specializing in autonomous systems and machine learning
Mid-level AI/ML Engineer specializing in FinTech and fraud detection
“ML/backend engineer with PayPal experience building high-stakes production systems, including a GenAI internal support assistant and a real-time fraud scoring pipeline. Strong in Python/FastAPI, model-serving infrastructure, RAG architecture, and production observability, with clear readiness to transition those backend patterns into a TypeScript stack.”
Junior Software Engineer specializing in full-stack development and applied ML
“Full-stack engineer with experience at Zoho and Amazon who has owned production systems end-to-end, including a monolith-to-microservices migration using Kafka and Cassandra that improved search latency ~25% and increased throughput without data loss. Also built a hackathon project (Buildwise) into a sold product for a construction company (AI-driven document compliance checks) and shipped an IoT-based parking availability MVP in 3 weeks.”
Director-level Data Science Manager specializing in ML forecasting, experimentation, and MLOps
“Data/ML engineer with experience at American Express and Amazon, owning an end-to-end rewards redemption/liability ML pipeline (~200GB) with rigorous regulatory/audit validation and quarterly executive reporting. Also built web-scraped product datasets with anti-bot protections at a startup and helped modernize an authn/authz service using AWS, plus led early-stage migration work from an internal warehouse to GCP with CI/CD and cloud observability.”
Senior Full-Stack/Data Engineer specializing in cloud data pipelines for legal and financial platforms
“Data/analytics engineer who built and operated a DocuSign-based real-time analytics platform end-to-end, processing 20–50k webhook events/day with ~99.5% reliability. Strong in idempotent event processing, schema-evolution-safe ingestion (raw JSON + dynamic parsing), and serving data via versioned, low-latency REST APIs with solid CI/CD and observability.”
Mid-level Software Engineer specializing in full-stack development and AI
“Frontend developer/designer who built an in-house real estate dashboard for Okhara & Company, owning the flow from Figma design through React implementation and production iteration. Worked in a small team environment, focused on turning complex backend outputs into usable, polished interfaces with responsive design, PWA support, and performance optimizations.”
Senior Software Engineer specializing in AWS data platforms and event-driven systems
“Capital One engineer leading the architecture and delivery of a large-scale AWS Glue/Spark/Delta Lake batch messaging pipeline that decoupled batch from real-time flows, added multi-region failover and automated retries, and delivered ~40% AWS cost savings with ~3x performance gains. Currently building an LLM-powered Slack bot using RAG to automate message investigations by querying CloudWatch, Snowflake, and internal documentation with privacy-aware masking of NPI/PII.”
Mid-Level AI Engineer specializing in data pipelines and scalable ML systems
“Data engineer/backend developer with experience owning end-to-end, high-volume data pipelines for ML/analytics using Python, Airflow, SQL, and PySpark, reporting ~30% error reduction through improved reliability and data quality checks. Has also built Django-based REST APIs with caching/pagination and strong versioning practices, and operated external data collection/web scraping pipelines with anti-bot measures, monitoring, retries, and idempotent backfills.”