Vetted Computer Vision Professionals

Pre-screened and vetted.

PM

Senior Embedded Systems Software Engineer specializing in ADAS, infotainment, and automotive platforms

Irvine, CA11y exp
KC SynergyUniversity of Central Florida
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NL

Mid-level AI Engineer specializing in LLM systems and data science

Chicago, IL3y exp
AbbVieUniversity of Illinois Chicago
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AP

Senior AI/ML Engineer specializing in computer vision, GenAI, and 3D spatial analytics

Baltimore, MD12y exp
Under ArmourNorth Carolina State University
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MS

Senior Machine Learning Engineer specializing in AI, NLP, computer vision, and GenAI

Somerville, NJ9y exp
NICEHamdard University
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MV

Mid-level AI Engineer specializing in healthcare and financial ML systems

5y exp
Blue Cross Blue Shield AssociationUniversity of Massachusetts Amherst
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WT

Mid-level Software Engineer specializing in full-stack systems, AI, and cybersecurity

Seattle, WA7y exp
T-MobileUniversity of Washington
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BA

Mid-level Software Engineer specializing in backend systems and healthcare IT

Northampton, MA4y exp
ScalaCodeWestern New England University
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KS

Senior Software Engineer specializing in embedded systems, simulation, and data science

Bedford, MA7y exp
MITREUniversity of Washington
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PR

Mid-level Software Engineer specializing in AI platforms and distributed systems

Austin, TX6y exp
OracleUniversity of Texas at Dallas
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KM

Kimberly Michela

Screened ReferencesStrong rec.

Junior Full-Stack Software Engineer specializing in web apps and developer tools

Toronto, Canada1y exp
Game of StreaksUniversity of Toronto

Frontend engineer who built the full frontend for gameofstreaks.com using React/Next.js with an emphasis on responsive design, accessibility, SEO, and performance profiling. Has experience refactoring legacy HTML/CSS/JS sites into reusable React components and shipping quickly with unit tests, CI/CD, and branch-based deployments; also collaborates with designers in hackathon settings (e.g., an AI interview practice app).

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BH

Bryan Holland

Screened ReferencesStrong rec.

Executive AI Product & Controls Engineering Leader specializing in agentic video editing and EV systems

SF Bay Area, CA11y exp
MAGICSEVEN AIUniversity of Michigan

Startup builder (MagicSeven) who designed and implemented a browser-based, agentic video editor end-to-end, including an AWS event-driven multimodal LLM “indexing” pipeline and an orchestration LLM agent for searching and manipulating footage. Demonstrates deep video file/codec knowledge plus practical production hardening of LLM workflows (format validation, plan/execute, S3-based state for debuggability).

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Sai Haritha Sardena - Mid-level Full-Stack Software Engineer specializing in web, cloud, and AI/ML in Remote, USA

Sai Haritha Sardena

Screened ReferencesStrong rec.

Mid-level Full-Stack Software Engineer specializing in web, cloud, and AI/ML

Remote, USA7y exp
Tylmen TechNorthern Arizona University

Software engineer with experience at Wipro and Tylmen Tech owning customer-facing onboarding and real-time features end-to-end (React + Spring Boot) and building TypeScript/React apps backed by Node.js microservices (MongoDB, RabbitMQ). Strong in production reliability and fast iteration: feature-flagged rollouts, idempotent APIs/consumers, DLQs, and SLO-driven incident tooling, including an internal QA & release dashboard adopted by engineering and support teams.

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NC

Nightvid Cole

Screened ReferencesStrong rec.

Senior Computer Vision & Sensor Algorithms Engineer specializing in imaging systems

Saratoga, CA7y exp
Early-Stage StartupUniversity of Maryland, College Park

Robotics/remote-sensing software engineer who built and validated multisensor image-processing and spectral chemical-detection pipelines (RX anomaly detection, ACE), including calibration protocols with a motorized shutter and rigorous data QC. Uses white-box NumPy simulators to debug SLAM/registration issues before translating logic to C++, and partnered with hardware teams to solve temperature-driven signal variation via combined software calibration and improved thermal management.

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MP

Mayank Pratap

Screened

Intern Robotics Engineer specializing in autonomous navigation and SLAM

West Lafayette, IN1y exp
Nanyang Technological UniversityPurdue University

Robotics software engineer with deep ROS2 Humble/Nav2 experience who built an SDF-based navigation system (RRT* global planning + gradient-based local avoidance) and implemented scan-matching localization. Proven real-time performance debugging and optimization on hardware (Unitree B1), including halving compute-cycle latency and resolving ROS2 jitter/message-drop issues through explicit QoS and executor/callback-group design.

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Mounika S - Senior Machine Learning Engineer specializing in MLOps and Generative AI in St. Louis, Missouri

Senior Machine Learning Engineer specializing in MLOps and Generative AI

St. Louis, Missouri7y exp
Emerson
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MS

Senior Software Engineer specializing in robotics, ML, and full-stack web development

Hillsboro, OR12y exp
IntelPortland State University
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JF

Mid-level AI/ML Software Engineer specializing in Generative AI and NLP

Remote5y exp
EmerjenceBoston University
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SD

Srijan Dokania

Screened ReferencesModerate rec.

Junior Robotics & Machine Learning Engineer specializing in perception, SLAM, and edge AI

Boston, MA2y exp
Field Robotics Lab (Northeastern University)Northeastern University

Built and deployed an Azure-based, fine-tuned CLIP visual retrieval system at Staples for a ~300k-item product catalog, improving edge-case recall by 12% by engineering a custom delta-similarity/dynamic-margin loss. Also has robotics experience using ROS2 for sensor/compute orchestration, including GPS-time-synchronized sensor triggering for robot swarms and latency-bounded optical-flow benchmarking for edge deployment.

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CZ

conghu zhao

Screened ReferencesStrong rec.

Senior Software Developer specializing in AR/VR, computer vision, and mobile graphics

Redmond, WA18y exp
NOMADGODigiPen Institute of Technology

Unity/C# engineer with hands-on experience building cross-platform VR/mobile prototypes at Verizon Labs, including a networked VR cinema and virtual office application. Particularly strong in performance engineering: they describe custom update architecture, shader work, and low-level iOS optimization that enabled 60 FPS while rendering HD video textures and running voice chat simultaneously. They also bring adjacent computer vision integration experience from Nomad-Go, with a practical focus on latency, inference/render separation, and data consistency.

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KP

Krishnapriyanka Ponnaganti

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer specializing in agentic AI and production ML systems

Atlanta, GA4y exp
KKRGENAI Innovations LLCUC San Diego

ML/AI engineer with hands-on experience shipping production computer vision and GenAI systems, including a fabric defect detection platform that combined vision models with agentic LLM workflows to reach 89% human-inspector agreement at 200 ms latency. Also built a RAG-based code QA tool for developers and emphasizes production monitoring, evaluation, caching, and reusable Python service design.

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