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Vetted AI & Machine Learning Professionals in Indiana
Pre-screened and vetted in Indiana.
Dan Ford
Senior Machine Learning Engineer specializing in on-device AI and large-scale deep learning systems
Vishakha Dikshit
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and document intelligence
Nasir uddin Khazi
Mid-level Machine Learning Engineer specializing in fraud detection and demand forecasting
Phani K
Mid-level AI/ML Engineer specializing in NLP, computer vision, and Generative AI
“Built and deployed a production LLM-powered clinical insights/summarization assistant for healthcare teams, including a Spark+Airflow pipeline, fine-tuned transformer models, and a FastAPI Docker service on AWS. Demonstrates strong MLOps/LLMOps depth (Airflow on Kubernetes, custom AWS operators/IAM, MLflow, CloudWatch) and practical reliability work like hallucination mitigation, confidence scoring, and retrieval-backed evaluation with shadow deployments.”
Kaushal Rathi
Mid-level AI/ML Engineer specializing in LLM agents, MLOps, and AI safety red teaming
Roshan Erukulla
Mid-level AI/ML Engineer specializing in NLP and Generative AI
“Built and deployed a production LLM-powered RAG assistant for healthcare teams (care managers/support) to answer questions from clinical and policy documentation, emphasizing trustworthiness via improved retrieval, reranking, and strict grounding prompts to reduce hallucinations. Also has hands-on orchestration experience with Apache Airflow for end-to-end ETL/ML workflows and applies rigorous testing/metrics (hallucination rate, tool-call accuracy, latency, cost) to ensure reliable AI agent behavior.”
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.”
Miheer Diwan
Junior Robotics & AI Engineer specializing in perception, planning, and manipulation
“Robotics software engineer who led the full perception/manipulation/planning stack for an autonomous watermelon-harvesting robot, including ripe-vs-unripe instance segmentation deployed on Jetson AGX Orin with TensorRT and quantization. Deep ROS 2 experience (custom ZEDx mask driver, LiDAR+stereo fusion, MoveIt 2/Nav2/ros2_control) and proven real-time optimization—cut latency ~40% and achieved consistent 7-second pick cycles in outdoor field conditions.”
Hrushikesh Attarde
Intern AI Engineer specializing in LLMs, MLOps, and cloud-deployed NLP systems
Onkar Saudagar
Junior AI/ML Engineer specializing in LLMs, RAG pipelines, and MLOps
Rukmini Pisipati
Junior AI/ML Engineer specializing in LLM automation and NLP
“Built and shipped a production LLM hallucination detection and monitoring pipeline using semantic-level entropy (embedding-clustered multi-generation variance) to flag unreliable outputs in downstream automation. Implemented a scalable async architecture (FastAPI + Docker + Redis/Celery) with strong observability (structured logs + PostgreSQL) and developed evaluation loops combining controlled prompts and human review; also partnered with non-technical stakeholders on AI-driven form validation/document processing.”