Vetted Computer Vision Professionals

“Robotics software engineer who built a ROS/C++ workcell stack to automate coating wooden panels with a 6-DOF arm, including trajectory generation, MoveIt/OMPL planning, and a single launch/config setup that runs in both Gazebo and on real hardware. Strong in debugging real-world planning failures (e.g., intermittent aborted/no-plan regions) through logging, planner swaps, and collision/kinematics tuning, and in designing modular ROS/ROS2 systems with versioned interfaces and translation layers for heterogeneous robots.”

“Deployment engineer at a robotics startup who owned end-to-end field deployments in greenhouse environments, including integrating humanoid robots (XArm 6), tuning perception stacks for real-world lighting shifts, and coordinating rapid fixes with hardware/software teams. Experienced debugging complex robotics integrations (LiDAR + NVIDIA Jetson + ROS2 + networking) and hardening solutions by automating configuration at boot, while also working directly with customers and training operators for ongoing support.”

“Backend engineer who built an Emergency Alert System with Virginia Tech for the City of Alexandria, focusing on real-time ingestion, secure dashboards, and AI-assisted prioritization. Emphasizes high-stakes reliability with guardrails (hybrid rules+LLM, confidence-based fallbacks), scalable async processing, and defense-in-depth security (JWT/RBAC plus database row-level security).”

“AI research engineer who has built and tested LLM agents end-to-end, including a Telegram real-time voice-to-typing assistant integrated with calendar scheduling. Emphasizes production concerns (security via mic-triggered activation, multi-model fallbacks, monitoring) and agent predictability using a GPT-3.5-based critic plus structured outputs (Pydantic) and ReAct-style orchestration.”

Akshay Bharadwaj Kunigal Harish

Screened

Mid-level Machine Learning Engineer specializing in NLP, computer vision, and LLM systems

Boston, MA5y exp

“Built a production multi-agent cybersecurity defense simulator orchestrated with CrewAI, combining Red/Blue team LLM agents, a RAG runbook retriever, and an RL remediation agent trained via state-space simplification and reward shaping for rapid incident response. Also partnered with quant analysts and fund managers to deliver an automated trading and portfolio management system using statistical methods plus CNN/LSTM models, reporting up to 15% weekly ROI.”

Ankush Desai

Screened

Junior Robotics Engineer specializing in ROS, perception, and robotic manipulation

2y exp

“Robotics software engineer focused on ROS2 autonomy stacks, with hands-on work spanning semantic 3D SLAM, sensor fusion, and controller customization. Built an indoor GPS-denied semantic SLAM system (>95% accuracy) and extended Nav2’s MPPI controller with a custom C++ critic to keep an agricultural rover centered in crop rows, boosting CO2 laser weeding effectiveness by 40%. Strong in simulation-to-real workflows (Isaac Sim, Gazebo Ignition) and deployment automation (Docker on Jetson Orin NX, GitHub Actions CI/CD).”

prashanth Jamalapurapu

Screened

Mid-level AI/ML Engineer specializing in data engineering, LLM/RAG pipelines, and recommender systems

5y exp

“Research assistant at St. Louis University who built and deployed a production document-intelligence RAG system (Python/TensorFlow, vector DB, FastAPI) on AWS, focusing on grounding to reduce hallucinations and latency optimization via caching/async/batching. Also developed a personalized recommendation system for the Frenzy social platform and partnered closely with product/UX to define metrics and iterate on hybrid recommenders and cold-start handling.”

Akhila Chitturi

Screened

Mid-level Embedded Software Engineer specializing in real-time control and automated testing

Detroit, MI3y exp

“Master’s thesis researcher building an intelligent fault diagnosis and predictive maintenance stack for autonomous quadcopters—covering simulation-based fault injection, signal processing (Id/Iq), ML fault classification, and real-time edge deployment on Raspberry Pi with Hailo-8 acceleration. Previously delivered production C++ middleware/microservices at Accolite and has hands-on experience with constrained networking via a LoRaWAN IoT communication stack.”

Anupam Sistla

Screened

Intern Software Engineer specializing in full-stack development, cloud, and automation

2y exp

“Robotics software engineer who built an autonomous debris-clearing rover software stack end-to-end using ROS 2, Python/OpenCV, and YOLOv3, with strong emphasis on real-time reliability (latency instrumentation, stale-data handling, watchdog fail-safes). Also implemented a Docker CI/CD deployment system for remote Raspberry Pi timelapse devices, distributing updates via AWS S3 to handle intermittent connectivity.”

Jaykumar Kotiya

Screened

Mid-level Machine Learning & AI Engineer specializing in Generative AI, NLP, and MLOps

Boston, MA6y exp

“Built and deployed production LLM systems for summarizing sensitive legal and financial documents, emphasizing GDPR-aligned privacy controls and scalable hybrid cloud architecture. Experienced with Kubernetes/Airflow orchestration and rigorous testing/monitoring practices, and has delivered measurable business impact (18% conversion lift) by translating AI outputs for non-technical marketing stakeholders.”

Thira Patel

Screened

Junior Robotics/Mechatronics Engineer specializing in SLAM, motion planning, and autonomy

1y exp

“Robotics software engineer focused on autonomy stacks for high-payload AMRs using ROS2/Nav2, with hands-on expertise in SLAM/localization and sensor fusion (RTK GPS, IMU, wheel odom, ZED2) to eliminate drift and stabilize real-time behavior on deployed hardware. Also built multi-robot coordination in ROS2/Gazebo and uses Docker + Git/CI-style testing to create reproducible simulation-to-hardware pipelines.”

Rakshith Baskar

Screened

Junior Robotics Engineer specializing in ROS2 perception and multi-sensor calibration

Mesa, AZ1y exp

“Entry-level robotics software engineer/team lead with hands-on experience spanning multi-robot UAV simulation (Gazebo + PX4 SITL) and autonomous vehicle stack integration (ROS2 Humble + Autoware Universe). Has tackled real-time perception optimization (OpenCV + custom deep learning) and built robust cross-protocol communication interfaces to connect ROS2 systems with embedded ESP32 devices.”

Aditi Deshpande

Screened

Mid-level Software/AI Engineer specializing in GenAI, AWS, and microservices

Remote, United States4y exp

“Built a production AI pipeline at EyCrowd to automatically grade shaky outdoor user-submitted brand videos using CV + CLIP/BLIP and a LangChain RAG layer per brand, with GPT-4 generating structured JSON explanations and grades. Optimized for latency and cost (batch PyTorch inference, caching), cutting review time from ~8 minutes to <2 minutes while reaching ~90% alignment with human graders and supporting thousands of videos/day.”

Kunal Sanghvi

Screened

Mid-level Data Engineer specializing in AI, NLP, and LLM systems

USA3y exp

“Built and deployed a production AI customer support chatbot at Unique Design Inc. using FastAPI, AWS, Docker, and retrieval-based grounding on internal documents. Stands out for hands-on ownership across discovery, deployment, incident debugging, and post-launch iteration, with a strong focus on making LLM systems reliable and safe in real business workflows.”

Raunak Bandyopadhyay

Screened

Intern-level Full-Stack Engineer specializing in AI and web systems

Amherst, MA0y exp

“Backend-focused intern in telehealth who combined engineering, QA leadership, and emergency infrastructure ownership. Built a text chat feature and an OpenAI-powered therapy chatbot, then stepped up to rebuild AWS infrastructure after it was accidentally deleted, while also improving chat responsiveness and reporting a 30% engagement lift.”

“Analytics candidate who has built full-stack data products end to end: from cleaning 1M+ retail transactions in MySQL to Python-based market basket analysis, churn segmentation, and Streamlit dashboards with Gemini-powered business recommendations. Also built a reproducible predictive modeling workflow for concrete strength forecasting, showing a blend of SQL, machine learning, and stakeholder-friendly delivery.”

Oleg Strakh

Screened

Executive robotics architect specializing in embedded AI and autonomous systems

Vilnius, Lithuania16y exp

“Founder of Workaholic-Robotics, a self-funded physical AI agriculture robotics startup, with hands-on experience spanning product development, customer discovery, commercialization, and fundraising prep. Brings a pragmatic, capital-efficient approach shaped by direct work with growers, dealers, and OEMs, plus accelerator experience through Innovate EU and Grishin Robotics Accelerator in London.”

“Robotics simulation/localization engineer who built a lunar crater navigation stack in ROS/ROS2 and Gazebo, including custom localization/perception/planning packages. Demonstrated strong debugging skills by using tf2 frame analysis to fix camera-to-base_link alignment, cutting heading error from 75° to 0.48°, and handled large NASA lunar imagery (~4GB) by converting/downsampling data for Gazebo.”

“Paid media performance marketer managing $50K+/month spend across Meta and Google for eCommerce and lead-gen, with a strong creative-testing orientation (UGC/video vs static) that produced ~25–30% lower CPA and ~35% higher ROAS when scaled. Builds full-funnel systems across Meta/TikTok (demand gen) and Google Search/PMax (high-intent capture), using marginal ROAS/CPA, frequency-based fatigue signals, and statistically grounded testing to scale or cut campaigns.”

“AI/LLM engineer with production experience building an LLM-powered investment recommendation system using RAG and chatbots, deployed via Docker/CI/CD and scaled on Kubernetes. Demonstrated measurable performance wins (sub-200ms latency) through QLoRA fine-tuning and TensorRT INT8/INT4 quantization, plus strong MLOps/orchestration background (Airflow ETL + scoring, MLflow monitoring) and stakeholder-facing delivery using demos and Tableau dashboards.”

“ML/computer-vision practitioner who shipped a CycleGAN-based bilingual handwriting translation demo (English↔Telugu) for low-resource scripts using unpaired datasets, focusing on preserving handwriting style and real-time deployment via Gradio. Also delivered a medical imaging pipeline by fine-tuning ResNet-50 and ViT-B/16 for pneumonia detection, emphasizing reproducibility, measurable evaluation, and stakeholder-friendly iteration.”

“Software engineer experienced delivering customer-facing, real-time industrial monitoring dashboards (motors/shafts/turbines) by partnering directly with end users to refine charts, alerts, and performance. Strong in API/platform integrations and production troubleshooting—uses feature flags, logging, validation/mapping, containerization, and performance testing to keep systems stable while iterating quickly.”

“LLM/RAG practitioner who has taken a support-ticket triage automation system from prototype to production, building the full pipeline (fine-tuned models, FastAPI inference services, vector storage, monitoring) and delivering measurable impact (~40% reduction in triage time). Demonstrates strong operational troubleshooting of LLM/agentic workflows (observability-driven debugging, fixing agent routing/looping) and supports adoption through tailored demos and sales-aligned technical communication.”

“Applied AI/ML engineer with hands-on production experience building a RAG-based AI assistant for pharmaceutical maintenance troubleshooting using LangChain + FAISS/Pinecone, including a custom normalization layer to handle inconsistent terminology and duplicate document revisions. Also built Airflow-orchestrated pipelines for document ingestion/embeddings and predictive maintenance workflows (SCADA ETL, drift-based retraining), and partnered closely with production supervisors/quality engineers via Power BI dashboards and real-time alerts.”