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Vetted Supervised Learning Professionals
Pre-screened and vetted.
Mid-level Backend Python Developer specializing in APIs, ETL, and transaction processing
Mid-level Machine Learning Engineer specializing in production ML, MLOps, and Generative AI
Mid-level AI/ML Engineer specializing in FinTech and production ML systems
Senior Software Engineer specializing in full-stack .NET and AI/ML systems
Sree Gautham Alluri
Mid-level Robotics & AI Developer specializing in autonomous navigation and LLM-powered robotic systems
“Robotics Support Engineer at HAI Robotics supporting a 385-robot warehouse fleet at a Shein client site. Built a production automation and reporting workflow to diagnose and resolve abnormal shelf locations, cutting incidents from ~250/day to ~25/day while providing actionable root-cause data to client/ops/maintenance. Hands-on ROS 2 (Humble) debugging across Nav2/localization/TF and sensor integration issues including QoS and firmware coordination.”
Shreevershith Kollabettu
Mid-level AI Engineer specializing in LLMs, agentic systems, and MLOps
“AI-focused engineer with Infosys experience building Azure/.NET chatbot applications and recent hands-on work with FastAPI/LangChain. Built a hackathon multi-agent legal counsel system showcasing agent orchestration, and emphasizes production readiness via Docker, GitHub Actions CI/CD, pytest automation, and adversarial simulations for auditable AI behavior. No direct robotics/ROS experience to date.”
sai anuragh Sangoju
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
“Built and deployed a production LLM-powered university support chatbot on Azure using a RAG pipeline, focusing on reducing hallucinations, improving latency, and handling ambiguous queries via confidence checks and clarification prompts. Also has hands-on orchestration experience (Airflow/Azure Data Factory), including hardening a demand-forecasting ingestion workflow with sensors, retries, and automated alerts, and uses a metrics-driven testing/monitoring approach for reliable AI agents.”
Yashwanth Penugonda
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production GenAI systems
“Built and deployed a production LLM-powered RAG knowledge system to unify operational/policy information across PDFs, wikis, and databases, emphasizing auditability and low-latency/cost performance. Improved answer relevance at scale by moving from pure vector search to hybrid retrieval with metadata filtering and reranking, and partnered closely with healthcare operations/compliance to define acceptance criteria and human-in-the-loop guardrails.”
Vamsidhar Vuddagiri
Mid-level AI/ML Engineer specializing in LLMs, MLOps, and Azure
“AI/ML engineer who led Impacter AI’s production deployment of a specialized outreach LLM (CharmedLLM) fine-tuned on GPT-4.1, cutting API costs ~40% while boosting outreach effectiveness ~60%. Built the supporting MLOps and data infrastructure (MLflow, Kubernetes, PySpark, Kafka) and has agentic AI experience from University of Dayton, using LangChain + RAG and vector search (Pinecone) to improve reliability and reduce hallucinations.”
Mid-level Data Scientist & AI Engineer specializing in NLP, computer vision, and MLOps
Mid-level Machine Learning Engineer specializing in healthcare and enterprise analytics
Sravani Gangaraju
Mid-level AI/ML Engineer specializing in NLP, computer vision, and recommender systems
“Built and deployed a production NLP sentiment analysis system at Piper Sandler to turn noisy, finance-specific customer feedback into scalable insights. Demonstrates strong end-to-end MLOps: fine-tuning BERT, improving label quality, monitoring for language drift, and automating retraining/deployment with Airflow and Docker (plus Kubeflow exposure).”
Mahesh Ponnam
Mid-level Data Scientist specializing in credit risk, fraud detection, and ESG analytics
“AI/LLM practitioner who has deployed production chatbots across e-commerce, HRMS, and real estate, focusing on retrieval-first workflows for factual tasks like product and property search. Optimized intent understanding and significantly improved latency by using lightweight embeddings and tuning the inference pipeline on Groq (Llama 3.3), while applying modular orchestration and measurable production evaluation.”
Othmane Benyoucef
Executive AI & Data Engineering Leader specializing in LLM, RAG, and agentic AI systems
“Founder of a consultancy for 14 years with extensive experience managing multiple clients and projects simultaneously. Interested in leveraging AI to solve operational challenges and is seeking exposure to the venture capital/studio/accelerator ecosystem despite no direct VC experience.”
Mid-level MLOps/ML Engineer specializing in LLMs and financial risk modeling
Mid-level Software Engineer specializing in AI and cloud-native data platforms
Mid-level Full-Stack Software Engineer specializing in Java/Spring Boot and React
Senior Data Scientist and Machine Learning Researcher specializing in NLP, LLMs, and MLOps
Mid-level Generative AI Engineer specializing in LLM, RAG, and multimodal enterprise solutions
Mid-level AI/ML Engineer specializing in Generative AI and RAG assistants
Mid-level Machine Learning Engineer specializing in healthcare and financial AI
Pranathi Kamisetty
Intern AI Engineer specializing in LLMs, NLP, and conversational search
“Student building a production trip-planning LLM agent (LangChain + Streamlit) that routes user queries across multiple tools (maps/places/Wikipedia). Implemented zero-shot multi-label intent detection with priority rules to handle multi-intent requests, and collaborates with a startup product manager to shape tone, features, and user experience.”