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Vetted Kubernetes Professionals
Pre-screened and vetted.
kunj Golwala
Junior Robotics Perception Engineer specializing in autonomous navigation and robot learning
“Robotics software/perception engineer with production AMR experience at Symbotic, building a real-time SKU case re-identification pipeline used in high-volume Walmart/Target warehouse operations. Strong in ROS2 + Docker deployments on Jetson (TensorRT quantization) and system-level performance debugging, including cutting inference latency from ~13s to ~2s through architecture changes. Also has lab experience integrating SLAM/MPPI/behavior trees for rule-compliant navigation and distributed perception-to-UR5e manipulation systems (MoveIt/ros_control) with multi-camera sensing and 3D reconstruction.”
Leela Tikkisetty
Mid-level Software Engineer specializing in ML platforms and cloud-native backend systems
“Software engineer with experience at Google and the City and County of San Francisco building production AI systems, including a RAG-based internal support chatbot and ML-driven ticket priority tagging. Has scaled data/ML platforms with Airflow on GCP (1M+ records/day, 99.9% SLA) and deployed multi-component systems with Docker and Kubernetes (GKE), using modern LLM tooling (LangChain/CrewAI, Claude/OpenAI, Pinecone/ChromaDB, Bedrock/Ollama).”
Sai Krishna Yemineni
Mid-level AI/ML Engineer specializing in healthcare NLP, real-time risk systems, and ML platforms
“LLM-focused customer-facing engineer who repeatedly takes document Q&A and agentic prototypes into secure, monitored production systems. Experienced in reducing hallucinations via RAG + guardrails, diagnosing retrieval/embedding issues in real time, and partnering with sales to run metrics-driven PoCs that overcome accuracy/security objections and drive adoption.”
Chetana Reddy Yellareddy
Mid-Level Software Engineer specializing in distributed systems and cloud-native platforms
“Backend/AI engineer who built and scaled an internal AMD semiconductor manufacturing microservice platform (SMR), reworking a synchronous lot-request workflow into an event-driven RabbitMQ/Celery/FastAPI pipeline. Diagnosed and fixed peak-load reliability issues using deep observability and Kubernetes autoscaling, cutting notification latency back to sub-second and reducing duplicates via idempotency/DLQs. Also shipped an LLM-powered natural-language search with schema-constrained JSON outputs and guardrails, plus a plan-execute-verify Jira bug-resolution agent that can propose fixes and raise PRs under restricted permissions.”
Yuqi Lei
Mid-level Software Engineer specializing in financial data platforms and quantitative research tooling
“Owned and built Bloomberg’s end-to-end bitemporal dividend & dividend-forecast data platform powering BQL for 400k+ terminal users. Architected real-time Kafka ingestion (5k–10k msgs/sec) across 100k+ tickers with strong correctness guarantees (PIT/bitemporal time-travel, immutable history to avoid look-ahead bias) and achieved sub-100ms p95 query latency through indexing and caching, deployed with Kubernetes + DLQ and robust monitoring.”
Sahithi K
Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines
“Data engineer with experience at Moderna and Block owning high-volume (≈10TB/day) production pipelines on AWS, using Kafka/S3/Glue/dbt/Snowflake with strong data quality and observability practices (schema validation, anomaly detection, CloudWatch monitoring). Also built external financial API ingestion with Airflow retries, throttling/token rotation, and schema versioning, and helped stand up an early-stage biomedical data platform with CI/CD and incident debugging.”
Jisvitha Athaluri
Mid-level AI/ML Engineer specializing in NLP, RAG, and MLOps
“Built a production LLM/RAG-based “model excellence scoring” system at Uber to automatically evaluate hundreds of ML models, standardizing quality assessment and cutting evaluation time from days to minutes on GCP. Also delivered an NLP document classification solution for insurance claims at Globe Life, partnering closely with compliance/operations and improving routing accuracy from ~85% manual to 93% with the model.”
Lalithya Manasa Patri
Senior Data Engineer specializing in cloud ETL and real-time streaming pipelines
“Data engineer with eBay experience owning end-to-end pipelines for real-time order and user behavior analytics at 10M+ records/day. Strong in PySpark/SQL transformations, Airflow reliability patterns, and production observability (CloudWatch), with measurable outcomes including improved data quality and 30–40% query performance gains. Also built Python data APIs for analytics/ML consumers with versioning and backward compatibility.”
Travoy Spelling
Senior Data Scientist / ML Engineer specializing in GenAI, LLMs, and NLP
“ML/NLP engineer focused on production GenAI and data linking systems: built a large-scale RAG pipeline over millions of support docs using LangChain/Pinecone and added a LangGraph-based validation layer to cut hallucinations ~40%. Also built scalable PySpark entity resolution (95%+ accuracy) and fine-tuned Sentence-BERT embeddings with contrastive learning for ~30% relevance lift, with strong CI/CD and observability practices (OpenTelemetry, Prometheus/Grafana).”
Rohith Sadanala
Mid-level Machine Learning Engineer specializing in Generative AI and MLOps
“LLM/agent engineer who has shipped production RAG chatbots in sustainability-focused domains, including a packaging recommendation assistant that standardized messy user inputs and used Pinecone-backed retrieval over product/regulatory data. Experienced orchestrating end-to-end ML workflows with Airflow and AWS Step Functions/Lambda, emphasizing reliability (property-based testing, circuit breakers, OpenTelemetry) and measurable performance (latency/cost). Partnered closely with non-technical leadership to ship 3 weeks early, driving adoption by 150+ businesses and ~20% reported waste reduction.”
Byron Pineda
Staff/Lead Data Scientist specializing in Generative AI, NLP/LLMs, and MLOps
“Lead Data Scientist (10+ years) with recent work in healthcare data: built production pipelines that unify EHR, genomics, and clinical notes using NLP (spaCy/BERT/BioBERT) and scalable Spark-based processing. Also led development of domain-specific LLM/NLP systems for chatbots and semantic search, deploying models via FastAPI/Flask and improving retrieval with FAISS-backed, fine-tuned clinical embeddings and RAG-style workflows.”
Cornelius O'Donnell
Director-level Engineering & Program Leader specializing in AI product platforms
“Technical Program Manager and one of three internal "founders" of HP’s Hardware-as-a-Service home printer subscription initiative, spanning DTC shipping, simplified setup, ink replenishment, and warranty coverage. Led roadmap definition/execution, scaled delivery rapidly to 15+ scrum teams (including vendors) with SAFe-like coordination and shared engineering standards, and drove key architecture trade-offs (building an interim subscription management service) to accelerate time-to-market by about a year.”
Akanksha Agrawal
Mid-Level Full-Stack Software Engineer specializing in event-driven data platforms
“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).”
Sarath Dunga
Mid-level Full-Stack Developer specializing in cloud microservices and AI/ML integration
“Full-stack engineer (~3 years) with eBay production experience building and operating high-scale, event-driven Python microservices for order processing and AI-powered recommendations (Kafka/Redis/FastAPI on AWS with Prometheus/Grafana). Also delivered polished React+TypeScript analytics dashboards and designed high-concurrency PostgreSQL schemas with significant latency reductions. Recently built AI-agent orchestration and an interactive node-based requirements dashboard for Siemens Polarion via MCP servers, improving user interaction by ~17.8%+.”
Vismay Patel
Senior AI & Machine Learning Engineer specializing in NLP, GenAI, and MLOps
“ML/GenAI practitioner with healthcare domain depth who built and deployed a production cervical-cancer EMR classification system using a hybrid rules + medical BERT approach, optimized for high recall under severe class imbalance and PHI constraints. Experienced running end-to-end production ML/LLM pipelines with Apache Airflow (validation, promotion/rollback, monitoring, retraining) and partnering closely with clinicians to calibrate thresholds and implement human-in-the-loop review.”
Rishitha Madipelli
Mid-level Software Engineer specializing in cloud-native distributed systems and streaming data
“Backend/product engineer with Tesla experience building and operating a real-time OTA update monitoring and fleet analytics platform at massive scale (telemetry from 3M+ vehicles). Delivered end-to-end systems across Kafka-based ingestion, TimescaleDB/Postgres analytics modeling, FastAPI/GraphQL APIs, and React/TypeScript dashboards, and handled production scaling incidents on AWS EKS during major rollout spikes.”
Anu Baluguri
Mid-Level Software Engineer specializing in cloud-native microservices and event-driven systems
“Full-stack engineer with production experience at Atlassian and Zoho, spanning GraphQL federation, React/TypeScript frontends, and cloud-native AWS/Kubernetes operations. Built and operated a federated GraphQL gateway with Terraform + CI/CD + observability, delivering major latency and integration-time improvements, and also designed high-volume Kafka data pipelines (10M+ events/day) with strong reliability guarantees.”
Ranganayak Meravath
Mid-level Generative AI Engineer specializing in RAG, agentic copilots, and regulated AI
“Senior engineer who built and productionized an Azure-based Enterprise AI Copilot for financial/compliance teams, focused on grounded, auditable answers with citations to reduce hallucinations in regulated workflows. Experienced designing multi-step agent orchestration and improving reliability through targeted iterations (e.g., fixing chunking/parsing to materially improve citation accuracy), plus building defensive pipelines for messy ERP/operational finance data.”
Hari Kiran Reddy Rommala
Mid-level Full-Stack Software Engineer specializing in cloud and data platforms
“Full-stack engineer with experience spanning Amazon IMDb and Northeastern’s NeuroJSON portal, combining consumer product work with complex scientific data applications. Built IMDb’s streaming providers feature—described as the company’s most impactful feature of 2023—and has hands-on experience with React/Angular, GraphQL, AWS, Python services, and production monitoring.”
Chitra Uppalapati
Entry-level Software Engineer specializing in full-stack and machine learning applications
“Built production Python data integrations and dashboard automation for incident analytics, with a strong focus on data quality, observability, and reliability for leadership-facing reporting. Also translated an ambiguous manual creator evaluation process at startup Spring into an automated predictive scoring feature, showing a blend of backend data engineering, test automation, and cross-functional product thinking.”
“Built end-to-end LLM/RAG systems for biological data and scientific literature analysis in a drug discovery setting, helping researchers explore disease insights and treatment hypotheses faster. Combines applied GenAI product work with strong production engineering, including monitoring, retrieval optimization, reusable Python services, and scalable deployment on AWS/Kubeflow.”
Anveshvarma Dantuluri
Mid Backend Software Engineer specializing in FinTech platforms
“Frontend-leaning full-stack engineer with hands-on experience building financial operations and transaction monitoring products from 0→1 through production scale. They stand out for owning React UI architecture, backend/API integration, and data-layer performance decisions while making pragmatic startup tradeoffs and improving features post-launch based on latency, error, and user feedback.”
Devika gade
Mid-level Full-Stack Developer specializing in FinTech and cloud-native applications
“Full stack developer with strong implementation ownership across cloud deployments, integrations, and AI-powered support automation. They have put LLM/RAG workflows into production with measurable impact—cutting first response time by nearly 40%—and show unusual depth in debugging non-deterministic AI incidents, improving observability, and turning messy document inputs into reliable API-driven pipelines.”
Arjun Kulkarni
Junior Software Engineer specializing in AI, LLM systems, and healthcare applications
“Product-minded full-stack engineer with experience improving performance, UX, and platform architecture across startups including SideShift, Curator, Congruence, and work on an AI coding assistant called Exec. Stands out for cutting messaging-system Redis traffic by roughly 95%, redesigning user flows for faster adoption, and building reusable multi-tenant systems and cross-platform APIs without over-abstracting.”