Pre-screened and vetted.
Mid-level Data Scientist specializing in ML, NLP, and cloud deployment
Senior AI/ML Engineer specializing in LLMs, NLP, and production MLOps
Senior Full-Stack Engineer specializing in cloud-native microservices and AI solutions
Senior Full-Stack Software Engineer specializing in React, React Native, and Spring Boot
Mid-level Data Scientist / ML Engineer specializing in NLP, GenAI, and cloud ML deployment
Junior Full-Stack & ML Engineer specializing in AI products and real-time systems
Mid-level AI Engineer specializing in production LLM, RAG, and agentic AI systems
Senior Data Scientist specializing in NLP, MLOps, and cloud ML platforms
Principal Automation Architect specializing in cloud DevOps, microservices, and MLOps
Mid-level Java Full-Stack Developer specializing in cloud-native microservices
Senior AI Python Engineer specializing in Generative AI and MLOps
Mid-Level Software Engineer specializing in .NET, Azure, and ML automation
“JavaScript/React/TypeScript engineer with hands-on open-source experience improving a hooks utility library—fixed a reported async race condition that reduced unexpected re-renders and added a debounced callback hook that became widely used. Brings a production-minded approach to performance and abstractions (APM/metrics-driven, DB/caching focus) with strong testing, documentation, and community support practices.”
Mid-level AI/ML Engineer specializing in healthcare, risk modeling, and MLOps
“Robotics software engineer who built a ROS Noetic-based perception-to-control stack for a pick-and-place robotic arm, integrating OpenCV/TensorFlow vision with motion planning and PID tuning. Demonstrated strong real-time debugging skills (rosbag, queue/latency fixes) and experience deploying reproducible robotics environments with Gazebo simulation, Docker, and GitLab CI.”
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and NLP
“Backend engineer who built and migrated a large-scale document intelligence platform used by legal, healthcare, and insurance clients, processing millions of pages. Experienced moving from a monolithic, LLM-heavy approach to a modular FastAPI service architecture with ML classification + RAG, strong validation/auditability, and enterprise security (JWT/OAuth, RBAC, PostgreSQL RLS) with zero-downtime incremental rollouts.”
Mid-level DevOps Engineer and CS researcher specializing in cloud automation and ML/quantum tooling
“Research-focused software engineer who builds performance-critical Python/C++ systems emphasizing correctness, state-transition precision, and distributed coordination. Created an automated simulation-based testing/validation framework for quantum programs that caught subtle logic/type errors early, reduced debugging time, and improved developer confidence through strong observability and scalable test generation.”
Mid-level Robotics & Software Engineer specializing in ROS 2 autonomy and ML
“Master’s-level IoT course project that the candidate helped evolve into a research lab effort by “ROSifying” a soil-fertility detection rover (autonomous navigation within a GPS geofence, sensor fusion, and rover-to-base-station telemetry via NRF24 to a Raspberry Pi dashboard). Also built a ROS/Gazebo vision-based teleoperation system using a SigLIP hand-gesture model mapped to geometry_msgs/Twist, and improved stability by instrumenting and filtering a latency-prone perception-to-control pipeline.”
Mid-level GenAI/ML Engineer specializing in agentic AI and RAG systems
“Backend/platform engineer who has owned a Python/FastAPI results API and deployed it on Kubernetes with Helm and GitHub Actions-driven CI/CD. Demonstrates strong production operations mindset across performance tuning, monitoring, safe rollouts/rollbacks, and phased migrations, plus hands-on Kafka streaming experience focused on ordering and idempotency.”
Mid-level AI/ML Engineer specializing in NLP, GenAI, and MLOps in healthcare and finance
“AI/ML engineer with CVS Health experience deploying production LLM systems in regulated healthcare settings, including a large-scale RAG solution (1M+ documents) built for compliance-grade, auditable policy/regulatory Q&A with strong anti-hallucination controls. Also delivered an NLP summarization system for physician notes/case narratives by partnering closely with non-technical care operations stakeholders and iterating via prototypes, dashboards, and feedback loops.”