Vetted C Professionals

“Worked on an AWS DynamoDB Journal team project building internal operator dashboards end-to-end, creating Java/Spring Boot APIs and integrating them into a Spring Boot/Thymeleaf/JavaScript UI to speed up debugging workflows. Has experience with data-heavy web apps and performance techniques (load balancing, caching, pagination, compression) plus hands-on debugging across unit/integration/E2E tests; also maintained and enhanced a React website at Global Spark.”

“Senior engineering/technology leader who has defined and delivered a multi-year roadmap to modernize platforms and embed AI, leading global teams through cloud-native and microservices migrations on AWS/Azure. Demonstrated measurable outcomes including 99.99% uptime, 40% fewer incidents, 25% faster delivery, 5x scalability, and $30M in new business opportunities, while scaling a 100+ person distributed org with strong OKR-driven execution and mentorship culture.”

“Software-focused candidate who built a data monitoring pipeline during a hedge fund internship, integrating real databases and an email API to notify teams when data was ready. Comfortable working through legacy/scrappy code and uses LLMs to accelerate comprehension and delivery, with an emphasis on thorough testing and clear communication with stakeholders/customers.”

“ML/LLM engineer who built and shipped an LLM-powered internal knowledge assistant at Meta, focusing on production-grade RAG to reduce hallucinations and improve trust. Deep experience with scaling and serving (FSDP/DeepSpeed/LoRA, Triton, Kubernetes autoscaling) and reliability practices (Airflow retraining, MLflow versioning, monitoring with rollback), including sub-100ms latency and ~35% GPU memory reduction.”

“McKinsey & Company ML/NLP practitioner who builds production-grade AI systems across sectors (notably healthcare and finance), including RAG/LLM solutions, entity resolution pipelines, and embedding-powered search with vector databases. Demonstrated measurable impact (40% reduction in data duplication) and strong MLOps/data workflow practices (Airflow, MLflow, Spark, AWS/GCP, Prometheus, CI/CD).”

“Backend/data engineer with production experience at Uber building a near real-time driver rewards service on AWS (FastAPI, PostgreSQL, Redis) with strong reliability and concurrency controls. Also delivered AWS Lambda/ECS containerized deployments with GitHub Actions CI/CD and cost governance, built AWS Glue ETL with schema-evolution handling, and drove a ~10x SQL performance improvement while owning incident response via CloudWatch.”

“Masters capstone lead for a search-and-rescue rover that maps earthquake-affected environments using ROS2, SLAM (Cartographer), Nav2, and computer vision (OpenCV/ArUco). Served as both project manager and systems/architecture integrator, debugging IMU-driven navigation issues via RViz and implementing an A*-based planning workaround; also designed a supervisor/robot-side architecture to scale toward multi-robot coordination.”

“Backend engineer at Samsara with prior Amazon internship experience; built an internal Python chatbot for documentation discovery with a full security model (authn/authz and credential-based response filtering) in a sensitive environment. Currently works on dashcam/device-backend systems, including feature-flagged migrations for audio alert behavior and resilient real-time gRPC streaming under unreliable cellular connectivity, while actively monitoring Buildkite/Toolshed CI/CD rollouts.”