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Vetted C++ Professionals

Pre-screened and vetted.

EM

Senior Creative Technologist specializing in XR, interactive installations, and real-time graphics

9y exp
FreelanceUCL
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XJ

Principal Systems & Software Engineer specializing in IVD/medical device compliance and genomics

Foster City, CA26y exp
Wuxing EpigenomicUniversity of Rochester
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AA

Mid-Level Software Engineer specializing in full-stack web and FinTech systems

San Diego, CA3y exp
WhovaUC San Diego
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PN

Mid-Level Software Development Engineer specializing in AWS serverless and backend APIs

Austin, TX5y exp
AmazonUniversity of Central Florida
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RC

Mid-level Robotics & Firmware Engineer specializing in continuum robotics and SerDes validation

San Jose, CA5y exp
AMDUniversity of Toronto
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KY

Junior Robotics & AI Engineer specializing in autonomous systems and machine learning

3y exp
University of PennsylvaniaUniversity of Pennsylvania
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DS

Junior AI/ML Engineer specializing in agentic AI and cloud optimization

Cupertino, CA1y exp
AdvantisUC San Diego
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SN

Mid-level Software Development Engineer specializing in backend systems and ML platforms

New York, USA2y exp
FlipkartNYU
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JO

Mid-Level Technical Game Designer specializing in gameplay systems and Live Ops balancing

Houston, TX4y exp
Respawn EntertainmentRice University
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WW

Entry-Level Software Engineer specializing in backend systems and cloud messaging

Mountain View, CA1y exp
NewsBreakRice University
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ML

Senior Technical Game Designer specializing in AI, combat systems, and VR

Burnaby, Canada10y exp
MetaCentre for Digital Media
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HA

Mid-Level Software Development Engineer specializing in AWS edge AI and generative AI apps

San Francisco Bay Area, California6y exp
Amazon
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KH

Kanishka Harwani

Screened ReferencesModerate rec.

Intern Robotics & Embedded Systems Engineer specializing in ROS2 autonomous mobile robots

New York, NY1y exp
New York UniversityNYU

Recent graduate with a prototyping/hardware engineering background who is building a ROS2-dependent swarm robotics system for transporting non-standard cargo using 3+ robots. Has hands-on experience integrating multiple sensor modalities (LiDAR, IMU, GPS, radar) and developing custom teleoperation ROS nodes, currently tackling networking/communication challenges in multi-robot coordination.

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PD

Pavan Devulapalle

Screened ReferencesModerate rec.

Mid-level Software Engineer specializing in cloud platforms and AI-integrated full-stack development

Seattle, WA3y exp
AmazonUniversity of Texas at Dallas

Backend engineer who built Flask-based internal APIs supporting GenAI-driven provisioning/diagnostics (Outpost/AWS Outposts-like environment), with deep hands-on optimization across Postgres/SQLAlchemy (2s to <200ms endpoint improvement). Experienced integrating ML/LLM workflows via AWS SageMaker and Bedrock, and designing multi-tenant isolation plus high-throughput Redis-backed background task pipelines (minutes to seconds).

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AT

Executive Technology Leader (CTO) specializing in digital products, cloud platforms, and AI/ML

New York, NY26y exp
MendGeorgia Tech

IoT/connected-device and SaaS product builder with deep connected health/telehealth experience, including patient care delivery and remote patient monitoring. In their current org, they expanded a nutrition product business by prototyping and piloting a digital pre/post-surgical coaching care-delivery service with real providers/clinics/patients, then building an MVP and taking it to market.

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GM

Gagan Mundada

Screened

Intern Machine Learning Engineer specializing in multimodal AI and evaluation benchmarks

San Diego, CA2y exp
McAuley Lab, UC San DiegoUC San Diego

ML-focused candidate with beginner ROS/ROS2 experience (custom pub-sub nodes; TurtleBot3 SLAM simulation debugging via topic inspection and transform/orientation checks). Has research/project exposure to LLM training approaches (GRPO with pseudo-labels using Hugging Face TRL on Qwen/Llama) and uses Docker/Kubernetes + CI/CD to run ViT saliency-attention/compression workloads on UCSD Nautilus infrastructure.

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AP

Senior Robotics Researcher specializing in SLAM and 3D computer vision

Pleasanton, CA9y exp
OmronNorthwestern University

Robotics software engineer (10+ years ROS/ROS 2) currently leading the perception stack for Omron’s AMR fleet, including a scalable factory SLAM system that combines vision with laser SLAM to handle corridor aliasing. Strong in real-time embedded optimization on NVIDIA Jetson (CUDA + profiling) and fleet-scale validation via multi-robot Isaac Sim scenarios (USD-to-ROS 2 bridging, Nav2 in crowded scenes). Also contributed to a cloud-native reality-capture/3D reconstruction pipeline at Hilti using Docker and Kubernetes.

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AG

Aman Garg

Screened

Mid-Level Full-Stack Software Engineer specializing in Python and React/TypeScript

San Francisco, CA5y exp
ZEISSGeorgia Tech

Built and shipped a map-embedding SDK (published to npm) for Walmart apps, solving key performance issues with real-time streaming (WebSockets) and Canvas rendering while prioritizing developer experience. Also applies LLM/agentic patterns in production workflows—using diagnostic agents and human-in-the-loop escalation to detect and resolve issues (e.g., voice agent loops caused by RAG API failures). Has sales-engineering experience supporting enterprise renewals, including a million-dollar contract renewal while at Siemens working with Ford stakeholders.

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VS

Junior Software Engineer specializing in full-stack development and applied ML

New York, NY2y exp
AmazonNYU

Full-stack engineer with experience at Zoho and Amazon who has owned production systems end-to-end, including a monolith-to-microservices migration using Kafka and Cassandra that improved search latency ~25% and increased throughput without data loss. Also built a hackathon project (Buildwise) into a sold product for a construction company (AI-driven document compliance checks) and shipped an IoT-based parking availability MVP in 3 weeks.

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CG

Charvi Gupta

Screened

Mid-level Software Engineer specializing in robotics autonomy and safety-critical systems

North Kingstown, RI6y exp
Regent CraftCarnegie Mellon University

Robotics software engineer working on an electric seaglider autonomy/perception stack on NVIDIA Orin, tackling multi-modal operating constraints (5–10 knots float mode up to ~100 knots flight). Previously built a ROS-based multi-robot search-and-rescue system, including navigation integrated with SLAM/task allocation/perception, and improved real-world performance by switching to a 2D planner with a velocity-obstacles controller to handle slip and timing uncertainty.

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SN

Mid-level AI/ML Engineer specializing in NLP, graph models, and MLOps for FinTech and Healthcare

Remote, USA5y exp
StripeKent State University

AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).

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LT

Mid-Level Software Engineer specializing in full-stack and backend systems

Albuquerque, NM5y exp
Liberty MutualUniversity of New Mexico

Backend-leaning full-stack engineer with experience at Liberty Mutual and Airbnb, building high-scale insurance claims systems (1M+ monthly transactions) and consumer booking/pricing services (120K–180K daily requests). Strong in transactional data integrity, PostgreSQL performance tuning, and production operations (Docker/Jenkins/AWS), with measurable UX/performance wins including ~2.3s page loads and significant runtime failure reduction.

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PP

Mid-Level Software Engineer specializing in distributed backend systems and cloud-native microservices

Seattle, WA5y exp
UberGeorge Mason University

Software engineer focused on data platforms and applied LLM systems: built an internal data quality monitoring layer to catch silent data drift and iterated post-launch after finding ~30% false-positive alerts, reducing noise via dynamic baselines and improved structured logging. Also shipped a production RAG-based internal knowledge assistant over Jira/Confluence with citations, confidence-based fallbacks, and nightly automated evals to prevent regressions.

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