Vetted GitLab Professionals

Abinav Anantharaman

Screened

Mid-level Robotics Software Engineer specializing in perception, sensor fusion, and motion planning

Boston, MA8y exp

“Robotics/Perception Software Engineer at Berkshire Grey who built and hardened a production ROS-based perception + supervision stack for autonomous trailer-unloading robots (RGB-D + LiDAR), including grasp/geometry estimation and segmentation. Diagnosed real-time behavior issues by instrumenting ROS pipelines, then implemented runtime RANSAC-based compensation for LiDAR yaw bias and TF-window validation; also supports containerized deployment on Kubernetes and is actively porting the system from ROS1 to ROS2.”

Darshan Togadiya

Screened

Mid-level Full-Stack Engineer specializing in cloud-native web apps

Rancho Cucamonga, CA5y exp

“Full-stack engineer in an early-stage startup who built an EV charger monitoring and payments dashboard from scratch, owning UI/UX (Figma), React frontend, Node/Postgres APIs, and production deployment/ops (Firebase + AWS). Demonstrated measurable impact (40% fewer reconciliation errors) and strong reliability chops through multi-source energy/payment ingestion, idempotent pipelines, and CloudWatch-driven incident resolution.”

“Backend/data engineer focused on production Python and AWS: built FastAPI REST services and a containerized ECS Fargate + Lambda architecture deployed via Terraform/CI-CD. Strong in data engineering (Glue/S3/Parquet/RDS) and operational reliability (CloudWatch/SNS, retries, schema-evolution handling), with experience modernizing legacy SAS reporting into Python microservices using feature flags and parity validation.”

“Senior product leader who helped transform Submittable from a single-program grant tool into a multi-program impact platform, driving ARR from $20M to $70M+ while improving retention and margins. Particularly strong in enterprise platform strategy and human-centered AI, with a clear philosophy of using AI to augment expert judgment rather than replace it.”

“Built and shipped a production LLM-driven data harmonization/record-matching pipeline for pharmaceutical datasets, combining normalization, embeddings/vector search, and an LLM validation step. Emphasizes production reliability via guardrails, confidence thresholds, idempotent/retryable stages, and human-in-the-loop fallbacks, with monitoring focused on manual review and error rates to reduce false positives.”

“Backend/data engineer with production experience building real-time sensor telemetry platforms: FastAPI + PostgreSQL services with strong observability, plus AWS serverless and Glue-based ETL into Redshift. Has modernized legacy SAS pipelines into Python microservices and delivered measurable performance wins (Postgres query latency cut to <1 minute and ~60% DB CPU reduction) while owning incident response and reliability improvements.”

“Unity/Meta Quest VR developer who helped ship a pharmaceutical lab-training simulator, owning key interaction systems (liquid transfer, pipette behavior) and building custom editor tooling to accelerate objective testing. Also built a solo early-lifeform simulation featuring procedural soft-body mesh generation and physics-driven animation, demonstrating strong systems/physics programming depth.”

“Backend-leaning full-stack engineer who has built and operated event-driven microservices platforms (FastAPI/React/TypeScript, Kafka, Kubernetes) and internal DevOps tooling. Delivered measurable impact through user-feedback-driven iteration (WebSockets update mechanism cutting redundant API calls ~30%) and operational improvements (deployment monitoring dashboard reducing rollback time ~40%), with strong focus on reliability, observability, and data consistency at scale.”

“Built and deployed an enterprise RAG application at Centene to help clinical teams retrieve insights from large internal policy document sets, cutting manual research by 30–40%. Implemented custom domain-adapted embeddings (SageMaker + BERT transfer learning) and hybrid retrieval (BM25 + Pinecone) to drive a 22% relevance lift, and ran the system in production on AWS EKS with CI/CD, MLflow, and Prometheus monitoring (99% uptime, ~40% latency reduction).”

PRAHARSHA JANDHYALA

Screened

Mid-level Data Scientist/Data Analyst specializing in ML, BI dashboards, and ETL pipelines

Dallas, TX4y exp

“Data/ML practitioner with experience at Humana and Hexaware, focused on turning messy, semi-structured datasets into production-ready pipelines. Built an age-prediction model from book ratings using heavy feature engineering and multiple regression models, and has hands-on entity resolution (deterministic + fuzzy matching) plus embeddings/vector DB approaches for linking and search relevance.”

Vivekananda Reddy

Screened

Mid-Level Full-Stack Software Engineer specializing in Java, React, and AWS

Dallas, TX4y exp

“Backend engineer focused on cloud-native microservices on AWS, owning Python/Flask ingestion services integrated with S3/Lambda and deployed via Docker/Kubernetes with CI/CD. Has led phased migrations from manually managed EC2 setups to automated CloudFormation + pipeline-driven releases, and designed event-driven near-real-time pipelines with idempotency, retry/backoff, and strong observability.”

Sai Nikhil Kanchukatla

Screened

Senior Software Engineer specializing in Golang microservices and IAM/SSO

Dallas, TX6y exp

“Backend engineer with experience at DigitalOcean and BNY Mellon, specializing in secure, highly available authentication and API platforms. Built an enterprise SSO system integrating Okta via OIDC with resilience patterns (gRPC contracts, circuit breakers, Kafka) and strong encryption, and led a careful monolith-to-Golang microservices migration using shadow traffic, dual writes, and feature flags to preserve data integrity.”

Bhavishyasai Chigurupati

Screened

Mid-Level Data/ML Engineer specializing in Generative AI and cloud data platforms

Overland Park, KS5y exp

“Built and productionized an LLM-based financial document analysis system using a RAG pipeline, including robust ingestion/chunking/embedding workflows, vector DB retrieval, and an AWS-deployed FastAPI service containerized with Docker. Demonstrates strong applied expertise in improving retrieval quality and latency at scale, plus hands-on experience debugging agentic/LLM workflows with monitoring and trace-based analysis while supporting demos and customer-facing adoption.”

Rupini Polavarapu

Screened

Senior DevOps Engineer specializing in AWS cloud infrastructure and CI/CD automation

Atlanta, GA10y exp

“AWS platform/infra engineer with hands-on ownership of EKS cluster lifecycle (upgrades, node scaling, networking/ingress, and EBS-backed stateful storage) and reliability validation using Datadog plus CI/CD smoke tests. Also supported on-prem VMware environments and operated a hybrid on-prem-to-AWS setup over site-to-site VPN, including incident response and implementing change-controlled firewall processes and proactive connectivity health checks.”

“Front-end engineer focused on sophisticated enterprise analytics dashboards for business and operations users. They combine strong React/TypeScript architecture with deep browser-performance knowledge and practical UX improvements for demanding expert users, especially in data-heavy applications with large tables, filtering, and role-based workflows.”

“Frontend engineer with experience building data-intensive, near real-time React/TypeScript applications in credit reporting and logistics tracking. Stands out for performance-focused architecture across dashboards and map-based products, including large dataset optimization, profiling, and Mapbox visualizations with live asset tracking.”

Baliram Maurya

Screened

Senior Full-Stack Engineer specializing in Java microservices and Healthcare IT

USA11y exp

“Backend engineer with hands-on experience modernizing healthcare platforms in a startup-like team of 8-12 across engineering, QA, DevOps, and product. They personally drove scalable Java/Spring Boot microservices for healthcare workflows, including FHIR integrations, real-time data pipelines, and resilient integrations with legacy and third-party systems.”

Saketh Kota

Screened

Mid-level Data Scientist / ML Engineer specializing in Generative AI, RAG, and MLOps

Irving, TX4y exp

“Built and productionized a RAG-based LLM research assistant for biomedical and regulatory document search using Mixtral 7B on SageMaker, LangChain, and Milvus, cutting research time by ~40%. Has hands-on multi-cloud MLOps experience across AWS/Azure/GCP with Kubeflow/Airflow/Composer plus Terraform + ArgoCD, and applies rigorous evaluation/monitoring (latency, accuracy, hallucinations). Also partnered with a non-technical PM to deliver an insurance policy Q&A chatbot that reduced customer response time by 30%+.”