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Vetted Latency Optimization Professionals
Pre-screened and vetted.
Senior Software Engineer specializing in AI, distributed systems, and computer vision
Senior Backend Software Engineer specializing in cloud-native microservices
Mid-level Prompt Engineer specializing in NLP, LLMs, and RAG systems
Senior Machine Learning Engineer specializing in LLMs, RAG, and agentic AI systems
Mid-level AI Engineer specializing in LLMs, RAG pipelines, and multimodal automation
Mid-level AI/ML Engineer specializing in LLMs, RAG, and cloud AI infrastructure
Junior Software Engineer specializing in cloud-native data systems and event-driven microservices
Mid-level AI/ML Engineer specializing in LLM, RAG, and semantic search systems
Senior Software Engineer specializing in LLM agents and RAG pipelines
Junior Software Engineer specializing in distributed systems and cloud infrastructure
Mid-level AI Engineer specializing in LLM automation and RAG systems
Swarag Reddy Pingili
Junior AI/ML Software Engineer specializing in LLM agents and RAG systems
“AI/back-end engineer at Canon who helped build and operate an internal production LLM platform that acts as a secure middle layer between users and models, defending against jailbreaks/prompt injection while enabling RAG, memory, and grounded responses over company data. Experienced with LangChain/LangGraph orchestration, vector DB retrieval, and reliability practices (testing, monitoring, adversarial prompts) to run high-throughput, low-latency AI workflows in production.”
DhanushKautilya Kammaripalle
Junior AI Integration Engineer specializing in LLM agents and RAG on cloud platforms
“Built and deployed LLM-powered features for a startup organizational management application, focusing on real-world deployment constraints like latency and cost. Implemented RAG with FAISS and improved retrieval quality by switching embedding models (OpenAI/Hugging Face) and fine-tuning embeddings on medical corpora for a medical-report UI feature. Uses LangChain and LangGraph to orchestrate multi-node LLM API workflows and evaluates systems with metrics like latency, cost per request, and error taxonomy.”
Vikesh Patel
Senior AI/ML Engineer & Data Scientist specializing in LLMs, RAG, and MLOps
“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.”
Sourabh Tiwari
Mid-level Robotics Software Engineer specializing in ROS2 autonomy and computer vision
“Robotics software engineer from Bigbot who led localization and perception for an outdoor autonomous delivery robot, building ROS2/Nav2-based autonomy with EKF sensor fusion (IMU/odometry/GPS) and perception-driven dynamic costmaps. Experienced taking systems from Gazebo simulation to real-robot deployment, optimizing real-time behavior via logging-driven debugging and latency reduction, and integrating heterogeneous comms (MAVROS/MAVLink, UART/CAN, MQTT) for distributed and multi-robot setups.”
Zueva Tatiana
Senior Software Engineer specializing in XR, 3D systems, and computer vision
“XR/Unity engineer with hands-on ownership of high-performance 3D reconstruction and visualization systems, including a Gaussian Splatting pipeline that improved target-device performance from ~20 FPS to 60+ FPS. Also brings multiplayer XR experience with Photon Fusion, cross-platform Quest/mobile shipping experience, and AI-driven NPC dialogue integration using a self-hosted rule-based backend. Based in Moscow and open to remote work across time zones.”
Adithya Sharma
Mid-level AI/ML Engineer specializing in MLOps, NLP, and Generative AI
“Built and deployed a production LLM-powered text-to-SQL/document intelligence chatbot on AWS that lets non-technical business users query complex enterprise databases in plain English. Demonstrates deep practical expertise in schema-aware prompting, embeddings-based schema retrieval, SQL safety/validation guardrails, and rigorous offline/online evaluation with human-in-the-loop approvals for risky queries.”
Ainesh Gunturu
Junior Data Analyst specializing in marketing analytics and machine learning
“Built and deployed a production LLM-assisted recommendation and insights platform that unifies structured, semi-structured, and unstructured data via a modular ingestion pipeline, canonical schemas, embeddings, and late-fusion modeling. Experienced in operationalizing ML/LLM systems with Airflow and Kubernetes (Dockerized services, autoscaling, rolling updates) and emphasizes reliability through layered testing, guardrails, monitoring, and A/B experimentation while partnering closely with non-technical stakeholders.”
Jaxon Repp
Executive Technology Leader specializing in distributed systems and multi-cloud infrastructure
“Early-stage builder who blends deep technical product work with go-to-market execution: created developer-focused platform tooling (Rust/Node/React) and at Harper moved from customer success into sales/partnerships, leading an Akamai partnership that ultimately helped close Walmart. Currently building a distributed application platform in Rust and iterating on macro-based abstractions to make Rust feel as approachable as Node.js; has not yet closed a seed round and is seeking a trusted operator counterpart.”
Areeb Abbasi
Mid-level Full-Stack AI Engineer specializing in deployed LLM agents and RAG systems
“Built a real-time AI meeting assistant using a Chrome extension that streams audio to a backend LLM workflow with transcription and RAG, then hardened it for production with queue-based streaming, async pipelines, security controls, and full observability. Also has hands-on startup sales experience, partnering with customers to define measurable technical win conditions (latency/accuracy) to close deals and drive adoption.”