Vetted Flask Professionals

Jayasri Guthula

Screened

Mid-level Applied ML Engineer specializing in LLM evaluation and multimodal agent systems

Remote5y exp

“Full-stack engineer working at the intersection of product and infrastructure, building developer-facing interfaces for AI voice agents in XR/immersive environments plus telemetry-heavy analytics dashboards. Experienced in Postgres telemetry data modeling and performance tuning, and in designing durable multi-step LLM pipelines with idempotency, retries, and strong observability; has operated in fast-moving startup-like teams (Biocom, HandshakeAI).”

“Analytics professional with hands-on experience turning messy Excel-based operational data into SQL/Python pipelines and Power BI dashboards, including a production bottleneck project that improved workflow efficiency by 20%. Also brings applied machine learning experience from a Databricks/PySpark loan risk scoring project using logistic regression and XGBoost on large-scale S3 data.”

Alex Archer

Screened

Staff Full-Stack Engineer specializing in Python, AI systems, and cloud SaaS

Anna, TX8y exp

“Full-stack startup engineer from a 20-30 person company who led a legacy monolith breakup into microservices, improving response times by 30% and database performance by 20%. Has hands-on experience across React/Next.js, TypeScript, Go, Python, and AI/data pipeline work, including building AI-driven platforms for freight and publisher-focused B2B SaaS products.”

“Backend/data engineer focused on AWS-based, low-latency event processing for market data and social-signal sentiment systems. Has led a monolith-to-event-driven migration with feature-flagged incremental rollout, and emphasizes production-grade security (OAuth2/JWT, secrets management, Supabase RLS) and data integrity (deduplication/idempotency) under high-volume spike conditions.”

“Backend Python engineer who has built an LLM agentic tutoring/assignment helper with a custom pipeline for parsing visually complex textbooks (integrating AlibabaResearch VGT and implementing missing preprocessing from the paper), improving RAG grounding with ~90% cleaner extracted text. Also led major platform scaling work by refactoring monolithic image processing into Celery-based async microservices on AWS (GPU/CUDA + S3), and implemented Kafka streaming for payment webhooks with strict ordering, idempotency, and multi-zone fault tolerance.”

“Backend/data engineer with aerospace telemetry and reporting experience across RTX and other orgs, spanning Python/FastAPI microservices, AWS serverless/containers, and AWS Glue-to-Redshift analytics pipelines. Has led legacy modernization with parallel-run parity validation and incremental rollout, and demonstrates strong operational ownership (monitoring, incident response, and cost optimization).”

“Software engineer with end-to-end ownership of a Qt/C++/QML desktop app for monitoring/configuring equipment, including hands-on UI performance optimization. Also built a web-based AI agent interface (React/TypeScript + Python Flask) with strong API contract discipline and async state handling, and improved microservices reliability using idempotency, DLQs, and observability. Created an internal CI/CD automation tool adopted across engineering and operations teams, adding safer rollbacks and better error messaging based on feedback.”

“Full-stack intern at Rebel who owned backend work on a cross-platform music platform using Python/Django with MongoDB, implementing user-focused REST APIs end-to-end. Also built CI/CD pipelines (Jenkins/GitHub Actions) to containerize and deploy to AWS, and has experience integrating Kafka-based real-time event processing with reliability and observability practices.”

“Healthcare-focused ML/LLM engineer who built a production hybrid RAG workflow to automate prior authorization by retrieving from medical guidelines/historical cases (FAISS) and generating grounded rationales for clinicians. Strong in operationalizing ML with Airflow/Kubeflow/MLflow on SageMaker, optimizing latency (ONNX/quantization/async), and reducing hallucinations via evidence-only prompting; also partnered closely with clinical ops to deploy a readmission prediction tool used in daily rounds.”

“Built a production lead-generation system using AI agents that researches the internet for relevant leads and integrates RAG-based contact enrichment/shortlisting aligned to existing CRM data, enabling sales reps to focus more on selling. Also has hands-on AWS data orchestration experience (Glue, Step Functions) moving raw data into Redshift and evaluates agent performance with human-in-the-loop plus BLEU/perplexity metrics.”

“UE5 gameplay scripter (Blueprint-focused) from small startup teams who specializes in setting up core project architecture (game loop/data flow, controller, game instance, UI/menu) and building modular systems reused across multiple games. Rebuilt a save-system architecture from scratch to replace a problematic asset and improve scalability/maintainability, and has hands-on performance optimization experience (profiling, level streaming, Nanite-to-LOD tradeoffs). Also implemented a realistic cricket match simulation using Markov chains and transition matrices.”

Hammad Ur Rahman

Screened

Senior DevOps Engineer specializing in cloud infrastructure and CI/CD

Boston, Massachusetts11y exp

“IBM Power/AIX engineer who has owned a 150+ LPAR AIX 7.x estate with VIOS/HMC/vHMC and PowerHA in production, including real outage and failover recoveries. Also brings modern DevOps/IaC experience—built Jenkins pipelines deploying to AKS and implemented Terraform on AWS with remote state, locking, and drift management.”

Oluwatobiloba Olajide

Screened

Junior Content & Technical Writer specializing in blockchain and crypto

Lagos, Nigeria2y exp

“Crypto/Web3 content marketer focused on SEO-driven growth and narrative storytelling, with a cited campaign generating 10,000+ clicks in under a week and a ~6% presale cap lift. Uses KOL/agency distribution plus on-chain and market signals (Dexscreener, wallet concentration, volume, supply) to spot early DeFi/RWA narratives and assess rug-pull risk, and tailors community-building tactics by platform (X, Instagram, TikTok).”

Vikram Sandigaru

Screened

Mid-level AI Engineer specializing in AI agents, RAG pipelines, and LLM evaluation

Boston, US3y exp

“Built and shipped production LLM systems at Founderbay, including a low-latency voice agent and a graph-based multi-agent research assistant. Strong focus on reliability in real workflows—hybrid SERP + full-site scraping RAG, grounding guardrails, validation checkpoints, and transcript-driven evaluation—plus performance tuning with async FastAPI, Redis caching, and containerization. Also partnered with a non-technical ops lead to automate post-call follow-ups via call summarization, field extraction, and tool-triggered actions.”

Nagendra Reddy Palugulla

Screened

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps

Florida, United States4y exp

“Built and shipped a production real-time content moderation platform for Zoom/WebEx-style meetings, combining Whisper speech-to-text with fast NLP classifiers and REST APIs to flag hate speech, bias, and HIPAA-related content under strict latency constraints. Demonstrates strong MLOps/infra depth (Airflow, Kubernetes, Terraform/Helm, observability) and a pragmatic approach to reducing false positives via threshold tuning, context validation, and hard-negative data—while partnering closely with compliance and product stakeholders.”

Kundhana Paruchuru

Screened

Mid-level Data Scientist specializing in ML, LLM pipelines, and MLOps

Remote, USA3y exp

“Built and deployed a production LLM-driven document understanding pipeline using LangChain/LangGraph, focusing on reliability via step-by-step prompting, validation checks, and monitoring. Also partnered with non-technical marketing stakeholders at Heartland Community Network to deliver an XGBoost targeting model surfaced in Power BI, improving campaign conversion by 12%.”

Jyothsna V

Screened

Mid-level Backend Software Engineer specializing in Python/FastAPI and cloud-native microservices

USA4y exp

“Backend engineer who evolved Coca-Cola bottlers' Trade Promotion Optimization platform at Coke One North America, building domain-focused microservices in Node.js and Python (Flask/FastAPI) with PostgreSQL. Experienced in multi-tenant security (OAuth2/JWT, RBAC, row-level scoping by bottler/region), API contract/versioning discipline, and Azure DevOps-driven incremental rollouts with strong observability.”

Ashay Panchal

Screened

Mid-level Software Engineer specializing in AI-driven distributed systems

San Jose, CA4y exp

“Backend engineer who built a high-stakes, privacy-first platform at be Still Analytics for survivors of domestic violence, emphasizing anonymity, security, and reliability. Experienced with GenAI backends (LangChain + AWS Bedrock) including RAG to prevent hallucinations, plus cloud-native scaling (Docker/Kubernetes) and cost-saving migrations from legacy VMs to serverless (30% reduction).”

Satish Kumar Reddy

Screened

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

Remote, NJ5y exp

“Built and deployed a production LLM/RAG intelligent document understanding platform for healthcare clinical documents (notes, discharge summaries, diagnostic reports), integrating spaCy entity extraction, Pinecone vector search, and a Spring Boot API on AWS with monitoring and guardrails. Demonstrates strong MLOps/orchestration (LangChain, Airflow, Kubeflow/Kubernetes) and a metrics-driven evaluation approach, and partnered with a healthcare operations manager to cut manual review time by 80%.”

Yash Amre

Screened

Intern Data Scientist specializing in machine learning and NLP

California, USA1y exp

“Analytics-focused early-career candidate with internship experience owning reporting and system performance analysis projects end to end. They combine SQL data preparation, Python automation, and dashboard delivery with measurable impact, including roughly 50% less manual reporting and about 20% better forecast accuracy.”

“Full-stack product engineer focused on data-heavy dashboard applications, with hands-on ownership from React/TypeScript UI through Node/Express APIs to Postgres schema design and optimization. Stands out for combining product sense with engineering rigor: improving onboarding and reporting flows using analytics and user feedback, while also building reusable upload infrastructure and safe multi-tenant configurable experiences.”

Keeravani Chekuri

Screened

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

Boston, MA3y exp

“Built and deployed an AI tutoring assistant end-to-end at Nexora School, spanning discovery with school districts, multi-agent LangGraph/RAG architecture, AWS Bedrock migration, and post-launch stabilization. Stands out for combining hands-on LLM systems engineering with strong educator-facing trust building, FERPA-driven architecture decisions, and disciplined production practices around evals, logging, and messy document ingestion.”