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Vetted Snowflake Professionals

Pre-screened and vetted.

SnowflakePythonSQLDockerAWSCI/CD
AB

Anish Babu Gogineni

Mid-level AI & Data Engineer specializing in RAG and analytics platforms

Remote, USA3y exp
Clarity VoiceUniversity of South Florida
Generative AILarge Language Models (LLMs)Data engineeringETLBatch processingApache Airflow+50
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VC

Vishal Chandra Gorremutchu

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

Peoria, IL3y exp
Bradley UniversityBradley University
Anomaly DetectionApache AirflowApache HadoopApache HiveApache KafkaApache Spark+131
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RR

Rohith Reddy Aleti

Junior Data Scientist / AI Engineer specializing in analytics, ML, and MLOps

Boston, MA3y exp
Humanitarians.AINortheastern University
PythonRSQLMATLABPySparkNumPy+78
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UK

Uday Kadali

Junior AI Engineer specializing in OCR and tax document automation

Irvine, CA2y exp
Clarkson UniversityClarkson University
PythonPandasNumPyScikit-learnTensorFlowPyTorch+55
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HT

Hemanth Taduka

Mid-level AI/ML Engineer specializing in LLMs, RAG, and agentic AI systems

Brooklyn, NY3y exp
CARA SYSTEMSNortheastern University
PythonSQLPyTorchTensorFlowScikit-learnAWS+65
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NK

Noellar Kappa

Junior Data Scientist specializing in cybersecurity and AI/ML

Saint Paul, Minnesota3y exp
ONCODEAUniversity of St. Thomas
AgileAmazon SageMakerAngularArtificial IntelligenceAuthenticationAWS+137
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MJ

Muskan Jain Jain

Junior Machine Learning Engineer specializing in deep learning and healthcare AI

Boston, MA3y exp
Amal Lab for Precision MedicineNortheastern University
A/B TestingAPI IntegrationAWSAWS GlueAWS LambdaBERT+84
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RP

RASHMITHA PAGADALA

Intern Data Scientist / ML Engineer specializing in predictive modeling and data pipelines

Hyderabad, India1y exp
National Remote Sensing CentreMontclair State University
PythonSQLRPySparkPandasNumPy+83
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PG

Phaneendra Ganji

Mid-level AI/ML Engineer specializing in cloud AI, MLOps, and NLP

Washington, USA4y exp
iLink DigitalFlorida Atlantic University
A/B TestingAgileAmazon DynamoDBAmazon S3Anomaly DetectionApache Airflow+126
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NS

Naga Sai Gowtham Mulam

Mid-level AI/ML Engineer specializing in MLOps, streaming data, and NLP/CV

USA4y exp
CGIUniversity of Central Missouri
Amazon CloudWatchAmazon ECSAmazon EMRAmazon KinesisAmazon S3Apache Hadoop+121
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DU

DHAWAL UMESH PANCHAL

Mid-level Data Analyst specializing in marketing analytics and machine learning

Columbus, Ohio4y exp
ElevateMeStevens Institute of Technology
A/B TestingAgileApache SparkAzure Machine LearningAzure SQL DatabaseBERT+79
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SM

Spandan Maaheshwari

Mid-level AI/ML Engineer specializing in GenAI, RAG, and multi-agent LLM systems

Boston, MA4y exp
PredictaBio InnovationsKhoury College of Computer Sciences (Northeastern University)
A/B TestingAmazon RedshiftAnomaly DetectionAWSAWS GlueAzure Data Factory+113
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JJ

Jaideep Janapati

Mid-level Data Engineer specializing in cloud data platforms and real-time pipelines

Denton, TX5y exp
Real DynamicsUniversity of North Texas
SDLCAgileWaterfallRPythonSQL+111
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AM

Aaron Mark

Senior Full-Stack Engineer specializing in Python, cloud-native microservices, and React

United States8y exp
TechLabScientists
PythonJavaScriptTypeScriptSQLDjangoFastAPI+77
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NJ

Nora Jaf

Senior AI/ML Engineer specializing in Generative AI and LLMOps

Washington, DC10y exp
Clarion Tech
A/B TestingAgileApache KafkaArgo CDAudit LoggingAWS+147
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RM

Ruthvika Mamidyala

Screened ReferencesStrong rec.

Mid-level Data Scientist specializing in GenAI, RAG, and predictive modeling

Hyderabad, India3y exp
TenXengageUniversity of North Carolina at Charlotte

“Backend engineer who built and evolved Python/FastAPI services (including AWS-deployed ML prediction APIs) for real-time profitability and risk insights at TenXengage. Emphasizes pragmatic architecture, strong validation/observability, and secure access controls (RBAC + row-level filtering), and has led safe migrations via parallel runs and incremental rollouts; reports ~20% forecasting accuracy improvement.”

PythonSQLPandasNumPyScikit-LearnTensorFlow+101
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PR

Pranava Reddy Kothapally

Screened ReferencesStrong rec.

Junior Data Engineer specializing in Azure, CRM data pipelines, and marketing personalization

Hyderabad, India2y exp
TechwaveCleveland State University

“LLM/AI engineer who has deployed production RAG conversational analytics and Text-to-SQL systems over Snowflake and curated data marts, emphasizing enterprise-grade guardrails for accuracy, security, and cost. Notable for a structured approach to reducing hallucinations (curated metric/table registry, SQL validation, RBAC, and citation-backed responses) and for building resilient, observable multi-step agent workflows using LangChain/LlamaIndex and Airflow.”

AgileAPI IntegrationAudit LoggingAzure Data FactoryAzure DevOpsBatch Processing+168
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VP

Vikesh Patel

Screened ReferencesStrong rec.

Senior AI/ML Engineer & Data Scientist specializing in LLMs, RAG, and MLOps

Eagan, MN8y exp
Intertech, Inc.Metropolitan State University

“ML/NLP practitioner who has delivered production systems in regulated domains, including a healthcare compliance pipeline using RAG (GPT-4/Claude) plus TF-IDF retrieval that increased document review throughput 4.5x. Also has hands-on experience improving fraud detection data quality via entity resolution (Levenshtein, Dedupe.py) validated with A/B testing, and building scalable, monitored workflows with Airflow, CI/CD, and AWS SageMaker.”

PythonJavaScriptNode.jsVue.jsTypeScriptGo+179
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SR

Swapnil Ramanna

Screened ReferencesModerate rec.

Mid-level Data Scientist specializing in Generative AI and Healthcare Analytics

3y exp
AdvocateIndiana University-Purdue University

“Built a LangGraph-based, tool-routing LLM chatbot to deliver fast, trustworthy investment-stock insights (including tariff impact) and deployed it to production on Snowflake after initially developing in Azure with AI Search and the Microsoft Agent Framework. Improved routing robustness by moving from LLM-based decisions to a deterministic router backed by schema-relationship graphs and YAML metadata, and ran the project iteratively with non-technical stakeholders over an 8-month engagement.”

A/B TestingAnomaly DetectionAWSCI/CDDeep LearningDocker+109
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KS

Karan Savaliya

Screened

Junior Backend Engineer specializing in data platforms and cloud APIs

Remote, USA1y exp
StealthIllinois Institute of Technology

“Backend lead at a stealth startup and builder of MailIQ/MailBox—an automated Gmail inbox digest + cleanup system. Designed secure multi-account email ingestion and cost-efficient LLM-based summarization, and implemented robust unsubscribe automation using Playwright + OpenAI webpage analysis (including captcha-handling) with strong safety guardrails, incremental rollouts, and rollback strategies.”

PythonJavaScriptC++KotlinNode.jsTypeScript+83
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AS

Ashish Shah

Screened

Mid-level Data Engineer / Software Engineer specializing in streaming and cloud data platforms

Arlington, TX3y exp
The University of Texas at ArlingtonUniversity of Texas at Arlington

“Backend engineer with deep Kafka/FastAPI microservices experience who redesigned a notification pipeline to cut end-to-end latency from ~5s to ~3s (including custom partition assignment and consumer tuning). Led a high-stakes ClickUp-to-Oracle migration of 1M+ records using idempotent ETL, reconciliation, and shadow deployment to achieve >99% integrity with zero downtime, and has hands-on production security implementation with Django/DRF (JWT + RBAC).”

PythonTypeScriptJavaScriptJavaSQLDjango+100
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SS

Santhi Sampath Gamidi

Screened

Mid-level AI Engineer and Data Scientist specializing in LLM agents and RAG systems

Palo Alto, CA5y exp
LemmataUniversity at Buffalo

“Built a production-grade LLM evaluation and regression system that stress-tests models across hundreds of iterations, combining LLM-as-judge, semantic similarity, statistical metrics, and rule-based checks, with results delivered via stakeholder-friendly HTML reports and dashboards. Experienced orchestrating multi-agent RAG workflows using LangChain/LangGraph and event-driven GenAI pipelines in n8n integrating OCR, speech-to-text, and external APIs, with strong emphasis on reliability, observability, and explainable failures.”

A/B TestingApache HadoopApache HiveApache KafkaApache SparkAWS Glue+149
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