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Vetted Docker Professionals
Pre-screened and vetted.
Mithilesh Gaurihar
Mid-Level Software Engineer specializing in Java microservices and cloud-native systems
“Full-stack engineer (SAP Labs experience) who built an end-to-end, real-time fraud detection system on Java 11/Spring Boot microservices with Kafka event streaming and a React/Redux analytics dashboard with WebSocket updates. Demonstrated strong production ownership by diagnosing a critical memory leak with Prometheus/CloudWatch + heap dumps and improving performance with Redis caching (40% faster queries), while also modernizing deployments via Kubernetes, Jenkins CI/CD, and Terraform.”
Chia-En Lu
Junior AI/ML Systems Engineer specializing in LLM infrastructure and distributed training
“Built and shipped a production NMT system translating medical documentation for a rare/low-resource language, tackling data scarcity with retrieval-driven pattern matching plus dictionary/grammar- and LLM-based augmentation and validating quality with a linguistic expert. Also develops agentic LLM workflows with LangChain/LangGraph (including a deep-research style system) and has experience aligning medical AI deployments with clinician-defined risk metrics and human-in-the-loop decision making.”
Advitha Bawgi
Junior Full-Stack Software Engineer specializing in cloud-native microservices
“Backend engineer with hands-on IoT and AI product work: built a decoupled Raspberry Pi + AWS IoT Core weather monitoring backend and a Dockerized FastAPI LLM service on AWS ECS using OpenAI/HuggingFace with an emerging RAG layer. Also delivered measurable performance gains at DAZN by redesigning event-driven/serverless ingestion (SNS, S3->Lambda->DynamoDB), cutting latency ~30% and boosting throughput ~25% while automating ~90% of manual sync work.”
Niteesh Ganipisetty
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and Computer Vision
“Built an LLM-powered learning assistant (EduQuizPro/EduCrest Pro) that uses RAG over URLs and PDFs to generate quizzes, notes, and explanations for students/professors. Emphasizes production robustness—implemented dependency fallbacks (FAISS/Sentence Transformers/Gradio), CLI-safe mode, and NumPy-based indexing—along with a custom orchestration layer to keep multi-step AI workflows reliable.”
Prateeksha Ranjan
Mid-level Software Engineer specializing in embedded AI and full-stack systems
“Robotics software engineer who built and owned core navigation components for a TurtleBot in ROS/ROS2 and Gazebo, including an RRT-based planner, waypoint-to-velocity motion planning, and PID trajectory tracking. Demonstrates strong real-time debugging skills (control-loop timing under CPU load), costmap/occupancy-grid tuning, and distributed ROS2 communication design using DDS/QoS, plus Docker and CI/CD automation experience from Keysight.”
Prateek Patil
Engineering Leader specializing in Digital Health, AI, and Cloud Platforms
“Senior Engineering Manager at Roche leading two Scrum teams building internally shared (“inner-sourced”) tools and libraries for a healthcare enterprise. Has led security/compliance-first architecture decisions (e.g., Python AI modules running inside a Java container) and front-end modularization (Angular monorepo to module federation), with a strong focus on developer experience via automated Swagger/OpenAPI documentation and robust testing/versioning practices.”
Ali Rahmati
Senior Machine Learning Engineer specializing in optimization, LLMs, and on-device AI
“Engineer with hands-on experience debugging and hardening a fixed-point implementation for an internal PoC, quickly diagnosing overflow/underflow issues that caused intermittent failures across thousands of runs and delivering a code fix. Comfortable presenting technical solutions with layered slide depth and doing follow-up deep dives for interested stakeholders, though has limited direct customer/sales partnership experience.”
Mounika Gunturu
Senior Python Full-Stack Developer specializing in cloud-native microservices and data platforms
“Backend/data engineer from Oliver Wyman who built and ran production Python (FastAPI) services on AWS (ECS/Lambda/API Gateway) supporting risk modeling and regulatory reporting. Strong in reliability/observability, Glue-based ETL with data quality controls, and legacy SAS-to-Python modernization with rigorous parity validation; also demonstrated measurable SQL performance wins and cost-control improvements in serverless scaling. Based in Raleigh, NC and can travel onsite for important Bethesda-area meetings.”
silin liu
Mid-level AI/ML Engineer specializing in LLM agents, RAG, and enterprise ML systems
“Built a production multi-agent recommendation/RAG system for internal data analysts to speed up weekly report creation by improving document discovery and automating report/SQL generation. Implemented LangGraph-based orchestration with deterministic agent routing, robust error handling (interrupt/resume), and metadata-driven semantic chunking for diverse PDF/document formats, plus monitoring for latency, throughput, and token/cost efficiency.”
Jahnavi Bellapukonda
Mid-Level Software Engineer specializing in full-stack web and cloud systems
“Full-stack engineer with strong data engineering and privacy-domain experience, having owned an automated Data Subject Rights (DSR) processing pipeline end-to-end across Azure SQL and GCP (GCS/BigQuery). Emphasizes production reliability via idempotency, validation checkpoints, structured logging/monitoring, and safe CI/CD-driven deployments, and has also built React+TypeScript + Node/Postgres web apps with scalable, maintainable architecture.”
Seyi R. Afolayan
Mid-level Robotics & Controls Engineer specializing in safe autonomy and perception-aware motion planning
“Robotics software engineer who built an open-source, real-time Cartesian controller for Universal Robots UR5/UR5e, targeting sub-mm accuracy at 500 Hz within ROS2/ros2_control. Demonstrates strong real-time debugging skills (timing profiling, singularity handling with Tikhonov regularization) and sim-to-real iteration using Gazebo/Isaac Sim plus physical hardware tuning; also has ROS1 experience building URDF/xacro and EKF configs for an underwater vehicle and has developed drone/robot packages.”
Jainum Sanghavi
Mid-level DevOps Engineer specializing in cloud automation and Kubernetes platforms
“Robotics/ML engineer who has built SO(3)-equivariant models for robotic manipulation, including custom equivariant layers and differentiable point-cloud rasterization/derasterization workflows. Also brings 2 years of DevOps experience in banking systems, automating CI/CD and infrastructure at scale (managed 180 OCI servers; reduced rebuild downtime by 80%).”
Shivam Udeshi
Intern Robotics/ADAS Engineer specializing in perception, sensor fusion, and state estimation
“Robotics software engineer who built a multi-agent dense warehouse mapping system in ROS 2, including LiDAR-camera fusion SLAM, timestamp-based synchronization, and DDS-based inter-robot pose/keyframe exchange under bandwidth constraints. Also applied Gaussian Splatting for selective photorealistic dense reconstruction and optimized real-time performance with node composition, bounded queues, and QoS tuning; experienced with Gazebo/CARLA/Unity simulation and Dockerized ROS 2 deployments.”
Swathi Sankaran
Senior Python Full-Stack Developer specializing in cloud, data engineering, and ML/GenAI
“Backend/data engineer with hands-on production experience building FastAPI services on AWS and implementing strong reliability/observability (CloudWatch, ELK, correlation IDs, alarms). Has delivered serverless + container solutions with IaC (CloudFormation/Terraform) and Jenkins CI/CD, and built AWS Glue/PySpark pipelines into S3/Redshift with schema-evolution and data-quality safeguards; demonstrated large-scale SQL tuning (45 min to 3 min on a 500M-row workload).”
Shravya Shashidhar
Intern Software Engineer specializing in LLM agents and full-stack development
“Embedded C++ engineer with Bosch automotive infotainment experience, owning real-time audio middleware modules with strict latency/memory constraints. Strong in profiling/optimizing deterministic behavior, debugging hardware-specific intermittent issues, and building automated test + CI pipelines; currently ramping up on ROS2 concepts (DDS, nodes/topics/services) to transition toward robotics.”
“Built and productionized an AI-native, agentic appeals decisioning system for health insurance operations, automating 500k+ scanned appeals/year. Delivered measurable impact by cutting review time from 12–15 minutes to ~3 minutes and auto-resolving ~85% of cases with strong auditability, evaluations, and human-in-the-loop guardrails, deployed as containerized microservices on Azure AKS.”
Charlotte Yu
Junior Full-Stack AI Engineer specializing in LLM apps and RAG systems
“Built and shipped a production LLM-powered “Vet agent” that automates pet symptom intake across multimodal inputs (images/files/text/speech) and provides analysis/home-care guidance, reaching thousands of daily active users within two months. Demonstrates strong agent engineering fundamentals: state-machine orchestration with structured JSON, tool/schema validation, high-availability routing/failover, and rigorous offline/online evaluation loops with trace-driven reliability improvements.”
John Ward
Executive Applications Development & Analytics Leader specializing in enterprise transformation
“Candidate has prior startup experience building systems and has firsthand experience with a venture that lost angel funding. They show thoughtful reflection on why the startup failed—emphasizing unclear success criteria, weak funding planning, and lack of team consensus—and would seek experienced advisors earlier in future ventures.”
Adrian Alvarez
Principal Cloud & Infrastructure Engineer specializing in reliability and regulated data platforms
“Founder/CTO-type startup leader who has built cloud-native data and AI platforms from scratch while owning both technical vision and product direction. Brings rare end-to-end startup experience spanning zero-to-one building, growth-stage execution, and fundraising from early stage through exit, with a strong ability to translate technical complexity into clear investor narratives.”
Fatim Majumder
Junior ML research engineer specializing in evaluation platforms and applied machine learning
“ML/LLM infrastructure engineer who built and shipped a production internal evaluation + failure-analysis agent (Arthur AI / R3AI context) that orchestrated end-to-end benchmarks with deterministic lineage, regression detection, and root-cause reporting at 5,000+ benchmarks/week. Also built backend observability and data validation systems for analytics pipelines at FullStory processing ~3.4B weekly events, emphasizing schema validation, quarantine fallbacks, and idempotent operations.”
Abhishek Adinarayanappa
Junior Software Engineer specializing in backend, cloud, and machine learning systems
“Built Digipulse, a university project that ingested and clustered Bluesky tweet data at scale and used Gemini to generate near-real-time topic summaries, processing 1M+ tweets per day. Also brings Intel experience with Prometheus and Kubernetes, including production monitoring and incident troubleshooting.”
Zahra Shergadwala
Junior Machine Learning Engineer specializing in AI, computer vision, and data systems
“Built and owned an end-to-end AV operations automation and dashboarding platform for USC event operations, used daily to coordinate hundreds of live events. Delivered a React/TypeScript full-stack system integrating Smartsheet APIs with strong reliability practices (typed contracts, validation/fallbacks, safe rollouts) and experience with queue-based microservice patterns (idempotency, retries, DLQs, monitoring).”
Darshan Patel
Mid-level Data Engineer specializing in financial and trading data
“Quant Data Engineer at ASX who is also building FinishKit, a full-stack SaaS that scans AI-generated codebases for bugs and production-readiness issues. Combines React/TypeScript, Supabase/serverless, Fly.io, and Postgres with strong product instincts, rapid iteration, and prior experience building secure multi-tenant data and dashboard systems across enterprise teams.”
Vidhi Chhatbar
Mid-level Full-Stack Engineer specializing in cloud microservices and FinTech
“Software engineer with experience across enterprise (AIG, MSCI) and an early-stage startup (Job Map), owning production systems end-to-end. Built secure insurance microservices on Spring Boot with JWT/RBAC and AWS-based CI/CD/observability, plus Kafka streaming pipelines for financial data. Also shipped a GenAI personalization MVP using FastAPI and LLM APIs in a high-ambiguity startup environment.”