Vetted OpenCV Professionals

“AI engineer with experience taking a GPT-4-powered GenAI career coach toward production on Azure AI Foundry, re-architecting the backend with hybrid (vector + keyword) search and RAG optimizations to cut latency by 50%. Also has client-facing TCS experience building healthcare ETL pipelines and delivering error-free monthly reports, plus current work analyzing agentic system reasoning traces and guardrail drift as an AI research fellow.”

“Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.”

Ashutosh Khatavkar

Screened ReferencesStrong rec.

Mid-level SDET/Software Engineer specializing in test automation and CI/CD

Syracuse, NY3y exp

“AAA game QA professional from Ubisoft (For Honor) with deep live-service multiplayer experience. Known for owning network/competitive integrity risks and building a custom network simulation tool to reliably reproduce desync issues, accelerating debugging and saving 100+ hours. Strong end-to-end QA process skills spanning test planning, triage, regression, and release verification using JIRA/TestRail.”

Urvish Shah

Screened ReferencesStrong rec.

Mid-level Robotics Software & Systems Engineer specializing in ROS2 multi-robot autonomy

Buffalo, NY4y exp

“Robotics software engineer with ROS2 multi-robot experience spanning decentralized signal source localization (LoRa RSSI on TurtleBot3) and a master’s-thesis project on collaborative object transportation with 4 robots. Strong in sim-to-real debugging—implemented noise modeling (RBF) and practical hardware/coordination fixes (CoG tuning, clock sync/flags) to make algorithms work reliably on real robots.”

“Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.”

Amrit Srivastava

Screened ReferencesStrong rec.

Junior Software Engineer specializing in robotics simulation and machine learning

3y exp

“Undergraduate AI/robotics research assistant who built a city-scale robotics simulation stack for embodied question answering, including JSON-driven environment generation and a ROS 2 pipeline bridging Isaac Sim sensors (CV/LiDAR) to external ML/RL algorithms. Also created and deployed an open-source library workflow tool adopted across multiple local libraries, using GitHub Actions CI/CD for signed releases and automated updates.”

“Robotics intern at the University of Delaware who built and debugged ROS2-based multi-robot coordination systems, focusing on real-time reliability (timestamp alignment, latency/jitter instrumentation, QoS/executor tuning). Also improved SLAM stability by fixing LiDAR/encoder synchronization and tuning state-estimation parameters, with a simulation-first workflow using Gazebo and Docker/CI for reproducible deployments.”

“ML/AI engineer with hands-on ownership of production recommendation and GenAI systems, spanning experimentation, deployment, monitoring, and iteration. Stands out for delivering measurable outcomes—22% CTR lift, 15% conversion lift, and a 30% reduction in support tickets—while demonstrating strong judgment on latency, cost, and safety tradeoffs in real-world systems.”

“Backend Python engineer focused on production-grade automation and reliability, with hands-on experience designing scalable API systems on PostgreSQL and making pragmatic architecture calls (modular monolith over premature microservices). Demonstrated measurable performance wins (50–60% latency reduction) and strong operational rigor via observability, incremental rollouts/feature flags, and security patterns like JWT + RBAC + database row-level security.”

Siva Pothuru

Screened

Mid-level AI/ML Engineer specializing in LLMs, MLOps, and cloud-native ML

San Antonio, TX5y exp

“LLM/agent engineer at USAA who built a production GPT-4o RAG conversational assistant for financial analysts, focused on regulatory interpretation and internal documentation search. Emphasizes compliance-grade reliability with strict grounding, safe fallbacks, and full auditability via MLflow/DVC plus human-in-the-loop review; reports ~45% reduction in ticket resolution time.”

“University Rover Competition autonomous-systems lead who architects and debugs a full ROS 2 autonomy stack (Nav2, vSLAM, EKF fusion) and backs it with strong engineering hygiene (Docker + GitHub Actions CI running headless Gazebo and colcon tests). Also has industry-facing ROS 2 hardware integration experience, building a ros2_control plugin for a Unitree G1 arm using CycloneDDS and optimizing real-time behavior via QoS tuning.”