Vetted CUDA Professionals

Pre-screened and vetted.

JH

Senior AI/ML Engineer specializing in LLM systems and MLOps

New York, NY11y exp
NexWEB LLCIndiana State University
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NR

Mid-level AI Engineer specializing in MLOps, GenAI, and enterprise ML platforms

5y exp
Bank of AmericaIndiana Wesleyan University
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RS

Junior Robotics Engineer specializing in reinforcement learning for autonomous driving

San Diego, CA2y exp
UC San DiegoUC San Diego
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AB

Senior Software Engineer specializing in mobile games, backend systems, and applied AI

8y exp
ZyngaGeorgia Tech
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SW

Mid-level Data Scientist specializing in geospatial computer vision and ML

Washington, DC6y exp
World BankGeorgetown University
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MD

Senior AI/ML Engineer specializing in healthcare AI, LLMs, and MLOps

Eden Prairie, MN15y exp
OptumUniversity of North Florida
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CW

Senior Data Scientist specializing in healthcare AI and clinical NLP

Miami, FL10y exp
University of MiamiBrunel University London
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TZ

Mid-level AI/ML Engineer specializing in computer vision and applied product engineering

5y exp
Elite Legal MarketingUniversity of Michigan
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HC

Junior Full-Stack Software Engineer specializing in ML, cloud infrastructure, and LLM agents

Austin, TX3y exp
SynopsysGeorgia Tech
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MG

Junior Robotics Software Engineer specializing in computer vision and ROS

Atlanta, Georgia2y exp
Georgia Institute of TechnologyGeorgia Tech
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YT

Intern Machine Learning Engineer specializing in recommender systems and financial risk modeling

Taipei, Taiwan1y exp
LangLiveUC San Diego
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YC

Junior Multimodal AI & Systems Engineer specializing in robotics and cloud infrastructure

Taichung, Taiwan2y exp
Shin-Da Information Co., Ltd.UCLA
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SW

Mid-level Data Scientist specializing in geospatial ML and NLP

Washington, DC6y exp
World BankGeorgetown University
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SG

Intern Software Engineer specializing in distributed systems and FinTech

Natick, MA2y exp
Goldman SachsUC Riverside
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NK

Mid-level GPU Software Engineer specializing in high-performance parallel computing

California, USA5y exp
UberOregon State University
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SZ

Siliang Zhang

Screened

Intern Machine Learning Engineer specializing in LLMs, RAG, and vision-language systems

Shanghai, China2y exp
CarizonUSC

Robotics ML/software engineer focused on Vision-Language-Action control for 7-DoF robots, replacing tokenized action decoding with continuous regression heads (including a logit-weighted expectation approach) to improve stability and real-time behavior. Strong in ROS1/ROS2 systems integration and debugging closed-loop manipulation issues via latency instrumentation, QoS-aware distributed messaging, and sim-to-real validation using Gazebo/Unity, Docker, and CI pipelines.

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SS

Shayan Shokri

Screened

Intern ML Engineer specializing in LLMs and NLP research

Seattle, WA0y exp
TruvetaCity University of New York

ML/LLM practitioner with experience at Truveta building an LLM-based evaluation framework; identified non-overlapping evaluator failure modes and proposed an ensemble approach that enabled scaling training data and drove ~5% performance gains across multiple internal projects. Strong focus on robustness to distribution shift (augmentation/domain adaptation/meta-learning) and production reliability via monitoring, drift detection, and safe fallbacks.

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IB

Isean Bhanot

Screened

Junior Robotics Engineer specializing in autonomy, perception, and motion planning

Los Angeles, CA3y exp
Laboratory for Embedded Machines and Ubiquitous Robots (LEMUR)UCLA

Robotics software engineer who built the full control stack for a fleet of manufacturing/repair robots in Relativity Space R&D (perception, planning, motion control, integration, deployment). Has ROS/ROS 2 experience spanning custom SLAM (LiDAR+IMU), multi-robot coordination, and multi-drone control (Pixhawk 4, minimum-snap trajectories), with strong real-world debugging and simulation/CI testing practices (Gazebo, CI/CD, some Docker).

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NC

Senior Full-Stack Engineer specializing in AI and cloud-native applications

Lakeland, FL8y exp
Revscale AIUC Irvine

Built and shipped a production LLM-powered internal developer tool that accelerated code reviews by about 30% while maintaining reliability through modular orchestration, validation, and monitoring. Demonstrates strong practical depth in agent architecture, backend workflow orchestration, and observability for non-deterministic AI systems, with concrete examples of reducing agent errors by 60%.

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DS

Intern Software Engineer specializing in cloud data platforms and full-stack systems

Seattle, WA1y exp
Amazon Web ServicesStony Brook University
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GK

Intern-level Software Engineer specializing in backend systems and applied AI

San Diego, CA1y exp
QualcommUniversity of Maryland, College Park
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