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Vetted Machine Learning Engineers in the Chicago Metro
Pre-screened and vetted in the Chicago Metro.
Yishi Wang
Junior Machine Learning & Data Science professional specializing in LLMs and analytics
“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”
Arun Yalamati
Mid-level AI & Machine Learning Engineer specializing in production ML and LLM applications
Vaibhav Bhandari
Mid-level Software Engineer specializing in backend systems and LLM applications
Prudhvi Angirekula
Mid-level AI Engineer specializing in LLM agents, RAG, and enterprise GenAI
Miguel Saldana
Senior AI/ML Engineer specializing in GenAI, MLOps, and healthcare analytics
Janvitha Mandyam
Mid-level GenAI/ML Engineer specializing in LLM applications and RAG systems
“GenAI/LLMOps practitioner who deployed a production RAG-based customer service and knowledge retrieval system for a global bank using LangChain, FAISS/Azure Cognitive Search, GPT-4/Claude, and Guardrails—driving a reported 35% Q&A accuracy lift while reducing handle time and escalations. Also partnered with non-technical leaders at CVS Health to deliver ML-driven supply chain risk and inventory insights via anomaly detection, NLG summaries, and stakeholder-friendly dashboards.”
sahithi sane
Senior Generative AI/ML Engineer specializing in LLMs, RAG, and MLOps
Vinay Yelalachinnolla
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and agentic RAG systems
Bindu Pathlavath
Mid-level AI/ML Engineer specializing in risk analytics and MLOps on AWS
Vamsi Koppala
Mid-level Machine Learning Engineer specializing in Generative AI and RAG systems
“LLM/ML engineer who has shipped an enterprise RAG-based Q&A system (LangChain/LlamaIndex, FAISS + Azure Cognitive Search, GPT-3.5/4 via OpenAI/Azure OpenAI) to production on Docker + Kubernetes/OpenShift, tackling hallucinations, retrieval quality, latency/cost, and RBAC/IAM security. Also partnered with operations leaders to turn manual reporting into an LLM-powered summarization and forecasting dashboard driven by real KPIs and iterative stakeholder feedback.”
Vigneshwaran Moorthi
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and Clinical AI
“Built and productionized a HIPAA-compliant LLM+RAG Clinical AI assistant at Optum, fine-tuning GPT/LLaMA on de-identified patient notes and integrating FAISS/Pinecone for sub-second retrieval; reported to cut diagnosis time by ~20 minutes per case. Experienced in orchestrating ML pipelines (Airflow, AWS Step Functions, Azure Data Factory) and in reliability techniques for LLM systems (grounding, citations, confidence filters, monitoring) while partnering closely with clinicians and compliance teams.”
Uday kumar swamy
Senior Machine Learning Engineer specializing in MLOps and NLP/GenAI
“Built a production LLM-agent framework for a startup that performs daily financial/trading analysis by combining live market data with internal tools, including a centralized memory module to prevent context drift and reduce hallucinations. Also implemented an Airflow-orchestrated retail price forecasting pipeline deployed to AWS endpoints, scaling parallel workloads via Kubernetes Executor and validating systems with rigorous functional + LLM-specific metrics and cross-team collaboration.”
Srikar Lakkimsetti
Mid-level Machine Learning Engineer specializing in insurance and healthcare AI
Sai Karthik Reddy
Mid-level AI/ML Engineer specializing in GenAI, NLP, and cloud MLOps
Kevin Patel
Mid-level Machine Learning Engineer specializing in Generative AI and MLOps
Vilas Jadhav
Mid-level AI/ML Engineer specializing in cloud ML, NLP/LLMs, and real-time data pipelines
kirthi chetla laxman
Senior AI/ML Engineer specializing in MLOps and Generative AI (LLMs/RAG)
Dhairya Desai
Senior AI/ML Engineer specializing in healthcare NLP and predictive analytics
“ML/NLP engineer with healthcare and industrial IoT experience: built an Optum pipeline that converted 2M+ physician notes into structured entities and linked them with claims/pharmacy data to create an actionable patient timeline. Deep hands-on expertise in production NER, entity resolution, and hybrid search (Elasticsearch + embeddings/FAISS), plus robust data engineering practices (Airflow, Spark, data contracts, auditability) and experimentation-to-production rollout via shadow mode and feature flags.”
Pavankumar Garikina
Mid-level AI/ML Engineer specializing in NLP, GenAI, and fraud/risk analytics
Sai Bharath Reddy Putlur
Mid-level Machine Learning Engineer specializing in healthcare and enterprise analytics
Sujay Surendranath Pookkattuparambil
Mid-level Machine Learning Engineer specializing in computer vision and reinforcement learning
“Early-stage engineer with hands-on embedded prototyping experience (Arduino/Raspberry Pi) who helped build an award-winning smart glasses project enabling phone notifications via Bluetooth. Strong computer vision performance optimization background, including accelerating 120 FPS inference by moving from TensorFlow to PyTorch and deploying through ONNX + TensorRT quantization, plus Docker-based GPU deployment and CI/ML practices.”