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Vetted Problem Solving Professionals

Pre-screened and vetted.

Problem SolvingPythonCommunicationSQLAgileGit
KS

Karan Shah

Screened

Mid-level Software & Robotics Engineer specializing in autonomous systems and ROS 2

USA3y exp
Boston DynamicsUniversity of Texas at Arlington

“Robotics software engineer focused on production-grade autonomy in GPS-denied environments, building full navigation stacks (perception, EKF/UKF sensor fusion, planning, control) in ROS2. Integrated YOLOv8/semantic segmentation/RL policies into real-time NAV2 pipelines via a custom perception-aware costmap layer, with emphasis on deterministic control loops, embedded GPU performance, and robust system observability/fault tolerance.”

PythonC++CROS 2LinuxGazebo+174
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AA

Akanksha Agrawal

Screened

Mid-Level Full-Stack Software Engineer specializing in event-driven data platforms

Bangalore, India5y exp
SAPUniversity of Illinois Urbana-Champaign

“Backend engineer with SAP experience modernizing a legacy Flask/PostgreSQL product master data platform into a modular, stateless, containerized service with Kafka-based background processing and improved observability. Also has hands-on academic/side-project experience operationalizing ML (NLP retrieval with TF-IDF/BERT via FastAPI and CV lane-edge detection inference APIs using PyTorch).”

AgileAngularApache CassandraAPI DesignAWSAWS Lambda+110
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RR

Rushi Reddy Lambu

Screened

Mid-level AI/ML Engineer specializing in Generative AI and MLOps

Remote, USA5y exp
McKinsey & CompanyUniversity of North Texas

“GenAI/LLM engineer and architect who built and deployed a production generative AI financial forecasting and scenario analysis platform at McKinsey, leveraging Claude (Anthropic), LangChain, Airflow, MLflow, and AWS SageMaker. Demonstrates strong LLMOps/MLOps rigor (monitoring, drift detection, automated retraining) and deep experience implementing global privacy controls (GDPR, differential privacy, audit trails) while partnering closely with finance executives and legal/IT stakeholders.”

PythonSQLRJavaC++Bash+192
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DP

Dony Permedi

Screened

Animation Director specializing in character performance and real-time previs

20y exp
NickelodeonSchool of Visual Arts

“Gameplay/cinematic animator and animation supervisor with 20+ years in CG across games, film/TV, VR/AR, commercials, and apps, including primary animation ownership on Louis Vuitton’s "Louis the Game" (Maya-to-Unreal). Strong real-time pipeline and mocap cleanup/export expertise (FBX), known for diagnosing issues like gimbal lock and coordinating with rigging/pipeline/Unreal teams; recently supervised an unreleased 8-minute Unreal-rendered cinematic trailer.”

Team LeadershipMentoringUnreal EngineUnityAdobe After EffectsAdobe Photoshop+61
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LL

Liz London

Screened

Senior Program Manager specializing in SAP CRM implementations and process transformation

Israel9y exp
Malam TeamTechnion – Israel Institute of Technology

“Post-sales SAP CRM implementation professional with experience at IBM and Malam Team, owning full lifecycle delivery from requirements and process design through configuration, testing, and end-user training. Notably built an SAP UI5 service center dashboard that cut SLA-miss tickets from 20% to 5% and regularly drove cross-functional alignment to unblock complex technical issues.”

Program ManagementProject ManagementRequirements GatheringStakeholder ManagementCross-Functional CollaborationProblem Solving+72
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SP

Sneha Patil

Screened

Mid-level Financial Analyst specializing in FP&A, forecasting, and regulatory reporting

New York, NY5y exp
JPMorgan ChaseUniversity of Texas at Arlington

“Backend-focused software engineer (4+ years) across e-commerce, banking, and healthcare who owned mission-critical checkout/order management end-to-end and improved peak-traffic success rates via resiliency patterns (timeouts/retries/caching) and data-driven iteration. Also built and shipped real-time operational dashboards (React/TypeScript + Spring Boot) using WebSockets and event-stream integrations, with strong experience in Kafka/RabbitMQ-style messaging at scale.”

ForecastingBudgetingRisk ManagementPredictive AnalyticsData AnalysisData Visualization+81
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SD

Sai Dinesh Pusapati

Screened

Senior AI/ML Engineer specializing in GenAI agents and LLM workflows

San Francisco, CA6y exp
Scale AIBelhaven University

“LLM/AI engineer with production experience building a retrieval-based document intelligence system that extracts information from PDFs/emails, backed by Python + Spark pipelines. Focused on reliability and cost/latency optimization (caching, batch processing) and has hands-on orchestration experience with Airflow (sensors, retries, alerts). Also partnered with business stakeholders to deliver customer feedback classification/summarization for faster sentiment insights.”

PythonTypeScriptJavaC#JavaScriptR+103
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VK

Vedant Kharwal

Screened

Intern AI/ML Engineer specializing in Generative AI and applied machine learning

Mumbai, India1y exp
LTIMindtreeBoston University

“New graduate with hands-on LLM work building a RAG pipeline (HNSW, lexical reranking/boosting, ReAct) and optimizing it through ablation to dramatically reduce latency. Also building a modular personal assistant with a custom wake word model, router-driven agent selection, and integrations like Spotify with secrets managed via .env.”

AlgorithmsAngularAPI DevelopmentArtificial IntelligenceAuthenticationBlender+93
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AG

Arun Gampala

Screened

Mid-level Full-Stack Developer specializing in MERN and AWS microservices

TX, USA4y exp
MetLifeSouthern Arkansas University

“Backend engineer with experience at MetLife and Amazon focused on security and control for internal and customer-facing services. Emphasizes contract-first Python/FastAPI APIs with strong auth (JWT + RBAC/claims), data-layer isolation (RLS/tenant scoping), and reliability practices like incremental refactors, rollback planning, and idempotency to handle retry-driven failure modes.”

ReactReact HooksReduxRedux ToolkitTypeScriptTailwind CSS+92
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AJ

Akhil Jaggari

Screened

Mid-level Full-Stack Software Engineer specializing in scalable web platforms and cloud microservices

CA, CA6y exp
UberUniversity of North Texas

“Backend engineer with fintech/real-estate lending domain experience (Berkadia) building Python/Flask services for indicative loan pricing across Fannie/Freddie workflows. Strong in scalable AWS architectures (S3, Lambda, SageMaker), database performance (PostgreSQL read replicas, indexing, pooling), and high-throughput optimizations (streaming exports, Redis caching) with measurable production impact.”

PythonObject-Oriented Programming (OOP)JavaCC++Angular+111
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WM

Will McEntee

Screened

Mid-level Operations & Analytics Professional specializing in logistics and sports data

Anaheim, CA4y exp
AmazonGeorgetown University

“Lifelong basketball player with extensive exposure to elite Southern California high school basketball (Servite/Trinity League) and familiarity with college recruiting through close connections, who applies a structured PFF-style evaluation lens to scouting. Comfortable identifying talent via film and in-person viewing and proactively engaging prospects through social media outreach; also brings experience working demanding overnight/on-call schedules from Amazon last-mile logistics.”

Microsoft ExcelPower BISalesforceSQLPythonR+52
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JA

Jeevan aher

Screened

Junior AI Engineer specializing in fraud detection, credit risk, and LLMs in FinTech

Remote, USA3y exp
JPMorgan ChaseUniversity of Illinois Urbana-Champaign

“AI engineer with production experience building a high-accuracy (98%) fraud detection system operating at real-time latency (1–2s) over millions of transactions, using a multi-model pipeline approach to meet performance constraints. Also implemented Airflow-orchestrated workflows (DAGs, retries, alerts) to replace brittle cron scripts and is currently pursuing a master’s project on real-time ASL-to-text conversion.”

PythonRSQLJavaScriptBashC+107
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KD

Kamlaker Dev Singh

Screened

Director-level XR/Immersive Technologist specializing in AI, AR/VR/MR and computer vision

Barcelona, Spain14y exp
MPS Interactive SystemsIIT Kanpur

“Unity VR/MR developer with multiple shipped Meta Quest projects, including a multi-user mixed-reality co-creation experience featuring real-time connection logic and shader-driven mesh generation for performance. Also builds AI-powered interactive applications, recently creating a video interview simulator using OpenAI API, HeyGen real-time avatars, and AWS audio/agent tooling while managing end-to-end latency challenges.”

CC#C++Computer VisionMentoringOpenCV+70
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HG

Harish Gaddam

Screened

Mid-level AI/ML Engineer specializing in LLM agents and RAG systems

Dallas, TX5y exp
VerizonUniversity of Texas at Arlington

“LLM/agentic systems builder at Verizon who deployed a LangGraph-orchestrated multi-agent ticket-automation platform with RAG (FAISS) to replace brittle rule-based bots. Improved routing correctness by ~30–40%, hit ~300ms latency targets via model routing, and reduced ops workload by ~60% through tight iteration with non-technical stakeholders and strong testing/observability practices.”

AWSAWS LambdaAutomationBackend DevelopmentCI/CDCollaboration+103
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RV

Ramyasri Veerapaneni

Screened

Mid-Level Full-Stack Developer specializing in FinTech

Remote, USA4y exp
IntuitMississippi State University

“Backend-heavy full-stack engineer with experience at Intuit (TurboTax Live) and Paytm payments, building and scaling Java/Spring Boot microservices for high-traffic transaction systems. Has hands-on wins improving peak-load performance using Redis/disk caching and Kafka event-driven patterns, plus React/Redux work for web app integration and strong monitoring practices with ELK.”

Apache KafkaApache SparkAPI DesignAWSCC#+83
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CL

Christopher Lim

Screened

Senior Full-Stack Engineer specializing in AWS-native backend modernization

San Francisco, CA9y exp
QualioGeorgetown University

“Backend/data engineer focused on compliance and statistical processing systems on AWS, building containerized FastAPI services plus event-driven async workflows (Step Functions/EventBridge) with strong reliability patterns (JWT auth, idempotency, structured logging). Has modernized SAS-based batch pipelines into modular Python/AWS services with parallel-run parity validation, and has demonstrated measurable SQL performance wins (40+ min to <10 min) and hands-on incident ownership using CloudWatch-driven detection and prevention.”

PythonJavaJavaScriptSQLNode.jsReact+102
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GR

Gagan Reddy Konani

Screened

Mid-level Machine Learning Engineer specializing in LLMs and RAG for healthcare

Remote, USA2y exp
MedtronicUniversity of Illinois Chicago

“AI Engineer (Medtronic) who deployed a production RAG-based clinical assistant grounded in curated biomedical literature (no patient-identifiable data). Deep hands-on experience orchestrating and hardening LLM workflows with LangChain/LangGraph, including stateful agentic flows, rigorous testing, and evaluation; reports a 72% accuracy improvement through retrieval enhancements (query rewriting, multi-query expansion, MMR reranking).”

AgileAmazon API GatewayAmazon DynamoDBAmazon EC2Amazon RDSAmazon S3+107
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AN

Apoorva Nanabolu

Screened

Senior Data Scientist / Generative AI Engineer specializing in fraud, risk, and MLOps

5y exp
PayPalUniversity of New Haven

“Built and deployed a production LLM/RAG fraud investigation system to replace manual investigator workflows, combining transaction data, historical cases, and policy documents with agent-style steps and LoRA fine-tuning. Demonstrates strong reliability engineering (grounding, citations, abstention paths), performance optimization (retrieval/indexing/caching), and end-to-end MLOps orchestration using Azure ML Pipelines/MLflow plus Kubernetes/Argo with canary and rollback deployments.”

PythonRSQLNoSQLSnowflakeBigQuery+178
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RR

Rodrigo Rosa

Screened

Mid-level GNSS/Robotics Software Engineer specializing in secure navigation and simulation

Munich, Germany3y exp
Airbus Defence and SpaceSapienza University of Rome

“Sole creator of a full-stack C++ 3D drone simulator/visualizer, including a self-contained flight stack (GNC, sensor simulation, flight manager) plus OpenGL-based graphics/UI. Built SITL-ready interfaces via MAVLink over UDP and ROS 2 Humble, and has embedded Linux CI/CD experience using CMake and Jenkins with automated unit/integration testing.”

CPythonMATLABGitJenkinsCI/CD+73
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SD

Sakshi Dinesh Deore

Screened

Mid-level Software Engineer specializing in AWS, DevOps automation, and data platforms

Bellevue, USA3y exp
AmazonUC San Diego

“Engineer with Securonix experience deploying and operating production microservices and real-time data-processing systems at high throughput. Led AWS infrastructure, CI/CD, monitoring, and customer-driven customization for a threat-report classification solution, including rule adjustments and model retraining based on live client feedback.”

AgileAmazon API GatewayAmazon DynamoDBAmazon EKSAmazon EMRAmazon S3+105
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KT

Keerthana Tammina

Screened

Mid-level Data Scientist specializing in machine learning and generative AI

Saint Louis, MO5y exp
DoorDashSaint Louis University

“ML/LLM engineer who has shipped a production transformer-based document understanding system on AWS, owning the full pipeline from domain fine-tuning to Dockerized CI/CD deployment. Demonstrates strong production rigor—latency optimization (distillation/quantization, async batching, autoscaling), orchestration with Airflow/Step Functions/Azure Data Factory, and monitoring/drift detection—plus experience translating ops stakeholder needs into adopted AI automation via dashboards.”

AgileAmazon RedshiftAmazon S3Amazon SageMakerAnomaly DetectionApache Hadoop+157
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SC

Sean Childress

Screened

Senior QA Analyst specializing in video game testing across console, PC, and mobile

Irvine, CA6y exp
AmazonFull Sail University

“Game QA professional with live production ownership on New World Aeternum (progression-driven connected rewards spanning UI, backend tracking, and live tuning) and experience on God of War Ragnarok. Emphasizes risk-based test planning, strong cross-functional triage grounded in player impact/live risk, and highly actionable Jira/TestRail practices (PAL titles, traceability, video/log evidence) to speed resolution and reduce late-cycle churn.”

Operations ManagementGraphic DesignAdobe PhotoshopBusiness DevelopmentQuality AssuranceProblem Solving+80
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JP

Jadorian Paul

Mid-level Quality Assurance Engineer specializing in test automation and reliability

Putnam, CT8y exp
CoachEmMIT
C++Computer visionData visualizationEclipseJavaJavaScript+42
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