Vetted Machine Learning Professionals

“ML/NLP practitioner focused on knowledge-graph-based retrieval for LLM question answering, including an urban/autonomous-vehicle decision-making use case. Built a hierarchical GraphRAG + vector database system and an entity-resolution pipeline that blends spatial and semantic similarity, validated using LLM-generated synthetic datasets; uses Python tooling like RDFLib, GraphDB, OpenAI APIs, and LangChain.”

“Built and deployed a production compliance automation RAG system (at Citi) that generates citation-backed, schema-validated risk summaries for regulatory document review. Emphasizes regulated-environment reliability with retrieval-only grounding, abstention, confidence thresholds, and immutable audit logging, plus orchestration using LangChain/LangGraph and Airflow. Reported ~60% reduction in compliance review effort while maintaining high precision and traceability.”

“ML/LLM engineer who has shipped production RAG systems (LangChain + HF Transformers + FAISS) with hybrid retrieval and cross-encoder re-ranking, deployed via FastAPI/Docker/Kubernetes and monitored with MLflow. Also partnered with wealth advisors at Edward Jones to deliver a client retention model with SHAP-driven explanations and a dashboard that improved trust, adoption, and reduced high-value client churn.”

“Backend/platform engineer with production ownership of high-volume transaction analytics and fraud monitoring services built in Java/Spring Boot. Has scaled data processing platforms (including healthcare datasets) and operated Kafka-based event pipelines with schema versioning, deduplication, and replay/backfill workflows, using strong observability via CloudWatch/Grafana and CI/CD with Jenkins.”

“Former President/CEO who led MyGov through a successful acquisition, now on sabbatical building ncognait LLC—an AI-enabled app studio with one product launched (Taistful) and another in private beta (AIDONIS). Focused on startup CTO/founding roles and highly opinionated about using agentic coding to dramatically compress product development cycles and compete with larger incumbents.”

“Early-stage/first sales hire profile with strong outbound motion and process-building experience. Self-sourced and closed a $2.8M Yahoo deal (8-month cycle) using a shared mutual plan to manage stakeholders and timelines, and has recent mid-market ACV wins selling Mapistry to environmental compliance managers by enabling champions to secure internal budget. Has also implemented MEDDICC and built foundational GTM assets (e.g., Quantcast’s first sales deck used in $2B+ of closed business).”

“Built and shipped a production browser automation LLM agent with a structured 4-stage workflow (plan/browse/extract/verify), emphasizing reliability via schema validation (Pydantic), constrained tool use, and contextual retry loops. Reports ~60% accuracy on the WebArena benchmark and monitors runs via console output and the Agno framework GUI, prioritizing accuracy over speed.”

“Data engineer with healthcare and enterprise experience (Molina Healthcare, Dell Technologies) building and operating high-volume batch + streaming pipelines across AWS and Azure. Strong focus on data quality (schema validation, fail-fast checks), reliability (monitoring/alerts, retries), and performance tuning (Spark/partitioning), with measurable runtime reduction and improved downstream trust.”

Kyle Holmquist

Screened

Senior Gameplay Engineer specializing in Unity/Unreal gameplay, AI, and narrative systems

11y exp

“Game developer with 13 years in the games industry who built a Unity VR feature using machine learning to recognize player-drawn spell symbols, training an accurate neural network from an existing dataset and solving tricky screen-space/world-space input constraints. Actively uses AI assistants for targeted code snippets and code review while emphasizing understanding over "vibe coding," and is interested in expanding into multiplayer/networking.”

Kutay Demiralay

Screened

Junior Controls & Autonomy Engineer specializing in robotics and trajectory optimization

Seattle, WA3y exp

“MS thesis work in the University of Washington Autonomous Controls Lab building a full quadrotor guidance/navigation/control stack, including high-fidelity dynamics modeling and an SCP trajectory optimizer made robust to wind via trust regions and MPC-style replanning. Also built an autonomous RC car using ROS on Jetson Xavier with ZED stereo/VIO, implementing perception (point cloud filtering/clustering) and state estimation while addressing real-time synchronization and latency challenges.”

ESHWANTH D. G

Screened

Mid-level Robotics Software Engineer specializing in autonomous perception and sensor fusion

CA, USA4y exp

“Robotics engineer with Honeywell and Tata Motors experience deploying ROS/ROS2 autonomous mobile robot fleets into live factory environments, integrating sensors, safety PLCs, and on-prem services. Known for solving end-to-end latency and stability issues (including network spikes under load) using gRPC, Docker, and improved diagnostics—cutting diagnosis time from hours to minutes and achieving sub-150 ms control response.”

Yaswanth Thota Thota

Screened

Mid-level Data Analyst specializing in financial risk and healthcare analytics

AZ, USA4y exp

“AI/ML engineer focused on real-time, production-grade LLM systems, with a robotics-adjacent mindset around latency/accuracy tradeoffs and modular pipelines. Built a scalable RAG-based assistant orchestrated as microservices on Kubernetes with Kafka async messaging, ONNX/quantization optimizations, and monitoring (Prometheus/Grafana), citing a ~35% hallucination reduction; has also experimented with ROS Noetic/Gazebo to understand ROS concepts.”

Prachika Agarwal

Screened

Senior Solutions Architect and Data Analyst specializing in cloud data platforms and experimentation

New York, NY4y exp

“Software engineer who built and scaled an internal automation/auditing tool for analyzing Google and Adobe tagging containers, adopted by 13 internal clients and saving ~15 hours per audit. Has experience shipping containerized, Kubernetes-orchestrated systems and integrating OpenAI APIs into an agentic chatbot feature (plus prior NLP chatbot work during a Cyber Peace Foundation internship).”

Bryan West

Screened

Senior Software Engineer specializing in AI, cloud infrastructure, and full-stack development

Chantilly, VA17y exp

“ML/NLP engineer who built a production system that converts large-scale unstructured text into a connected, searchable knowledge base using spaCy + Sentence Transformers/FAISS and a Neo4j knowledge graph, with BERTopic and XGBoost for organization/labeling. Strong focus on production-grade Python workflows (FastAPI/Celery, Pydantic validation, Docker, AWS ECS/Lambda) and robust entity resolution with measurable precision/recall and human review for low-confidence matches.”

Preetham Reddy Konuganti

Screened

Junior Full-Stack Engineer specializing in AI applications and scalable web platforms

San Jose, CA2y exp

“Full-stack engineer with customer-facing delivery experience who built and deployed a multi-platform social media automation product (Next.js/Node/MongoDB) and optimized it using BullMQ/Redis background jobs, retries, and rate limiting for reliable posting at scale. Also delivered an AI-powered false-positive analysis service in a cybersecurity context, resolving production pipeline stalls via log-driven debugging, parallelization, caching, and LLM guardrails.”

Young Joon Suh

Screened

Senior Research Scientist specializing in AI for autonomous driving and semiconductors

Seoul, Korea5y exp

“Robotics perception engineer focused on autonomous driving 3D detection, integrating PETR embeddings into BEVFormer and tackling hard orientation/temporal alignment issues in multi-camera BEV pipelines. Uses Gazebo with custom sensor plugins to validate calibration, timing, and transforms, and blends synthetic labels with real imagery for scalable 3D box generation.”

Narendhiran Saravanane

Screened

Junior Robotics Software Engineer specializing in ROS 2, controls, and applied AI

Denver, USA2y exp

“Robotics software engineer with 2+ years across ROS1/ROS2 projects spanning humanoid behavior engines and agricultural robots. Built an LLM-driven, ROS2-lifecycle-based decision system plus micro-ROS firmware on Teensy for modular sensors/motors, adding health monitoring that improved reliability 10x. Strong simulation/testing and deployment discipline (Gazebo, 95% coverage, Docker + AWS Greengrass/ECR, CI/CD) and demonstrated localization expertise with EKF sensor fusion achieving <0.5% error.”

Divyansh Agarwal

Screened

Junior Machine Learning Engineer specializing in computer vision and LLM applications

New York, NY3y exp

“Built and led an autonomous driving software effort for Formula Student, owning the full autonomy stack (perception, planning, control) orchestrated in ROS. Implemented stereo depth + YOLO object detection, RRT/RRT* planning, and a robust SLAM pipeline (Kalman filter, submapping) while leveraging Gazebo simulation and modern deployment tooling (Docker/Kubernetes, AWS, GitHub Actions CI/CD).”

Utkarsh Gupta

Screened

Junior Robotics & ML Engineer specializing in perception, navigation, and VLA models

Los Angeles, CA1y exp

“Robotics software engineer with hands-on AGV/AMR experience at ERIC Robotics, building ROS2-based LiDAR perception and localization on NVIDIA Jetson for real-time deployment. Improved unstable localization in challenging environments (e.g., tunnels/bushes along rail tracks) via scan-matching, filtering, and consistency checks, and cut latency by moving from rclpy to rclcpp and leveraging CUDA. Comfortable across the stack from simulation (MuJoCo/Isaac Sim/Gazebo, domain randomization) to deployment tooling (Docker, basic CI) and distributed ROS2/DDS systems.”

Jeetendra Girish Vasisht

Screened

Junior Software Engineer specializing in cloud-native microservices

Bangalore, India2y exp

“Backend engineer (Nokia) who designs and migrates cloud-native microservices at scale, including a secure low-latency system handling 500k+ daily transactions. Strong in Kubernetes/OpenShift operations, CI/CD standardization, and production security (OAuth2/JWT/RBAC) with SOC2-aligned controls and zero critical security incidents. Demonstrated expertise in safe migrations (canary/blue-green, dual writes, reconciliation) and concurrency correctness in real-time systems.”

Sai Chatrathi

Screened

Mid-level AI/ML Engineer specializing in healthcare analytics and MLOps

NY, USA4y exp

“Built and deployed a production LLM-powered lesson adaptation platform for K–12 educators that personalizes content for multilingual and neurodiverse students using RAG and content transformation. Owned the full stack from FastAPI backend and OpenAI integration through reliability/safety controls, latency/cost optimization, and weekly shippable modular APIs, iterating directly with curriculum stakeholders to reduce hallucinations and improve educator trust.”

UMESH KAMISETTY

Screened

Mid-level Data Engineer specializing in cloud lakehouse and streaming platforms

Seattle, WA5y exp

“Data engineer focused on building production-grade pipelines on AWS (Kafka/Kinesis/Glue/S3) through to curated serving layers in Snowflake and Delta Lake. Emphasizes automated data quality validation (PySpark + CI/CD), modular dbt transformations for analytics (customer spending, risk metrics), and operational reliability with CloudWatch and DLQs; data consumed by BI tools and ML pipelines for fraud detection and risk analytics.”

“Data/streaming engineer in capital markets who led an end-to-end trade settlement data product (Kafka→MongoDB→data lake) with rigorous data-quality logic and ~$175K first-year operational impact. Also built a low-latency Go-based CME market data engine feeding SOFR curve generation, using MSK on EKS with performance tuning (idempotency, compression, partitioning) to achieve sub-100ms delivery.”