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Vetted Machine Learning Professionals
Pre-screened and vetted.
“Built and shipped a production-grade RAG-powered news summarization and Q&A product, tackling real-world issues like retrieval drift, hallucinations, latency, and autoscaling deployment (Docker + FastAPI + Streamlit Cloud). Experienced in end-to-end ML/LLM workflow automation using Airflow, Kubeflow Pipelines, and MLflow, and has demonstrated business impact (40% inference precision improvement) through close collaboration with non-technical stakeholders at Evoastra Ventures.”
Tejaswini E
Entry-level Software Engineer specializing in computer science and applied ML/IoT
“Built a community cleanliness reporting Android app focused on helping citizens and volunteers report illegal waste dumping through maps, image uploads, and real-time updates. Stands out for combining modern Android UI architecture, Firebase-backed real-time features, and practical performance tuning for lower-end devices while keeping the experience simple for general public users.”
Akshay Amudhan
Entry Machine Learning Engineer specializing in quantitative finance and DeFi
“Built and deployed a production RAG chatbot using a vector database + LangChain-orchestrated pipeline, focusing on grounded, context-aware responses. Demonstrates practical trade-off thinking (retrieval quality vs latency/cost), hallucination control, and iterative improvement through logging, manual review, and stakeholder feedback loops.”
Intern/Junior Software Engineer specializing in full-stack web development and machine learning
Junior Full-Stack Developer specializing in React, Node.js, and AI/ML
Intern Full-Stack & Machine Learning Developer specializing in MERN and real-time systems
Intern Software Engineer with web development and machine learning project experience
Entry AI Engineer specializing in machine learning, computer vision, and data mining
Entry-Level QA Tester specializing in manual and API testing
Intern Web Developer specializing in system testing and technical documentation
Entry-level Product Manager and AI/ML Engineer specializing in agentic AI
richi ibnu wardana
“Built an automated ML/NLP document classification system for unstructured legal documents, combining classical models (TF-IDF + logistic regression/random forest) with entity resolution via fuzzy matching validated by precision/recall. Also implemented semantic similarity search using sentence embeddings stored in FAISS and improved matching by fine-tuning a transformer on domain-specific data and tuning similarity thresholds for fewer false positives.”
Intern Machine Learning Engineer specializing in NLP, RAG, and time-series forecasting
Mid-level Data & Machine Learning Professional specializing in analytics and automation
Sujay Godala
Entry-level student leader and developer specializing in FinTech and AI
“Student leader with a mix of technical and business exposure: built AI-powered projects like PETQuest, served as President of FBLA and DECA, and led outreach for a Finance Club. Stands out for combining hackathon coding success (top 1-3 placements) with leadership experience managing and organizing activities for 200+ students.”