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Vetted Research Assistants in Indiana
Pre-screened and vetted in Indiana.
Antara Bhavsar
Mid-level Software Engineer specializing in cloud-native systems and Android development
“Application-focused software engineer with experience at Amazon and Motorola shipping production systems ranging from developer monitoring/on-call tooling (Alcazar, ~40% MTTR improvement) to consumer AI features used by 100K+ users. Currently building an AI/ML-driven platform with a Python/FastAPI backend on AWS (ECS/RDS/S3) and has handled real production latency/scaling incidents end-to-end.”
Junior Software/Data Science Researcher specializing in AI, distributed systems, and GPU optimization
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and document intelligence
Anooshka Bajaj
Junior Data Scientist and ML Researcher specializing in Transformers, multimodal AI, and autonomy
“Autonomous robotics student who built an end-to-end ROS2 semantic goal navigation system as a solo course project, integrating CLIP-based vision-language understanding with SLAM Toolbox and Nav2 to execute natural-language commands in Gazebo/RViz. Also implemented and tuned an RRT planner from scratch in Python and uses Docker plus GitHub workflows for reproducible, tested robotics codebases.”
Sanjay Jayalakshmi Prabakar
Mid-level Robotics Engineer specializing in surgical robotics, teleoperation, and reinforcement learning
“Robotics software engineer with hands-on experience across reinforcement learning and ROS/ROS2, including a project teaching Boston Dynamics Spot to open a door by combining vision-based pose estimation with SAC-trained IK and a walking policy in MuJoCo. Previously built ROS Noetic control for surgical robots using RCM with MoveIt IK and achieved sub-0.02s latency via threading; also participated in a NASA ROS2 space simulation building rover teleop and sensor-driven mapping.”
Mid-level Robotics Engineer specializing in robot control, teleoperation, and reinforcement learning
Mid-level Computer Vision Researcher specializing in multimodal segmentation and UAV imagery
Prashanth Sankaranarayanan
Entry-Level Robotics Researcher specializing in autonomous vehicles, SLAM, and motion planning
“Robotics/AV engineer with strong ROS2 and autonomy stack integration experience, including bringing Autoware Universe up on a real Lexus autonomous vehicle platform. Also built a hierarchical reinforcement learning proof-of-concept for Boston Dynamics Spot (navigation + manipulation) and tackled sim-to-real challenges by implementing PD torque conversion for Jetson-based hardware; improved localization accuracy via GNSS+EKF fusion with a reported 28% drift reduction.”
Drashti Patel
Junior Software Engineer and ML Researcher specializing in full-stack and applied deep learning
“LLM engineer who built a production-style educational questionnaire generation system (MCQs/fill-in-the-blanks/short answers) using Hugging Face models (BERT/T5) and implemented grounding, decoding tuning, and post-generation validation to control hallucinations and quality. Also developed a "tech care" assistant chatbot with a custom Python orchestration/router layer (intent classification, context management, multi-step flows) and a structured testing/evaluation approach including expert review and automated checks.”
Jitesh Kumar S
Junior Machine Learning Engineer specializing in NLP, computer vision, and MLOps
“ML/LLM engineer with Meta experience building production AI systems for near real-time user-report classification and summarization under strict latency (<250ms), safety, cost, and privacy constraints. Has hands-on MLOps/orchestration experience (Airflow, Spark, MLflow, Kubernetes, Docker, GitHub Actions) plus observability (Prometheus/Grafana) and applies rigorous evaluation, staged rollouts, and A/B testing to keep agent workflows reliable in production.”
Amogh Arya Munipalle
Junior Software Engineer specializing in cloud, DevOps, and applied AI security
“Founding engineer who built a multi-tenant AWS backend from scratch focused on ultra-fast, configuration-driven client onboarding and low operational cost. Automated tenant provisioning/deployments with Terraform + GitHub Actions (new client infra in ~13 minutes) and scaled to 62 production clients handling ~75k requests/day without a major rewrite. Hands-on with migrations (DynamoDB->MongoDB), reliability/observability, and performance tuning (indexes, Redis, queueing, connection management).”
Junior Robotics & Computer Vision Programmer specializing in autonomous perception
Intern AI Engineer specializing in LLMs, MLOps, and cloud-deployed NLP systems
Mid-Level Full-Stack Developer specializing in MERN and AR/VR applications
Abhishek Ingle
Junior Full-Stack & AI Software Engineer specializing in React/Next.js and LLM systems
“Backend engineer with hands-on experience building low-latency, high-concurrency real-time chat on AWS (Node.js/Socket.IO/MongoDB) and improving reliability under unstable networks, contributing to ~40% user adoption growth. Also built FastAPI-based AI assistant context retrieval (RAG) APIs with embeddings/vector search, and has strong production experience in rate-limit handling, async refactors with safe rollout, and Supabase Auth/RLS optimization.”
Sai Harsha Kurapati
Mid-level Backend Engineer specializing in distributed systems and industrial IoT
“Backend/Python engineer focused on real-time sensor/IoT analytics: built dashboards and a high-throughput ingestion pipeline (MQTT -> Python worker -> TimescaleDB) with buffering, batch inserts, and validation. Strong Kubernetes + GitOps practitioner (Dockerized microservices, HPA, probes, ArgoCD) who has handled production incidents like CrashLoopBackOff under peak load and supported an on-prem analytics migration to AWS using shadow traffic and rollback plans.”
Entry-level AI Engineer specializing in NLP, RAG, and backend systems
Junior AI/ML Engineer specializing in LLMs, RAG pipelines, and MLOps
Junior Data Scientist specializing in LLMs, RAG, and multimodal AI
Md Rifat Ullah
Mid-level AI/ML Engineer specializing in NLP, GenAI, and conversational AI
“Built and deployed a production bilingual (Bengali/English) AI virtual assistant that replaced IVR for telecom customer service at massive scale (~15M users), integrating ASR/TTS, Rasa dialogue management, and custom NLP. Overcame low-resource Bengali data and noisy call-center audio with synthetic data augmentation and transformer fine-tuning, achieving significant production gains including ~50% reduction in support calls.”