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Vetted Machine Learning Professionals
Pre-screened and vetted.
Junior Full-Stack Data Engineer specializing in data pipelines and analytics
Junior Full-Stack Software Engineer specializing in SaaS and FinTech systems
Junior Full-Stack Developer specializing in web apps, cloud, and cybersecurity
Felix Aldi I Simanjuntak
Intern QA / Junior Web Developer specializing in manual testing and Laravel
“Console-focused QA tester with hands-on PlayStation (PS4/PS5) functional/compliance testing experience, including TRC-driven validation, stability checks, controller input testing, and performance dip investigation in combat-heavy scenarios. Also tested a Nintendo casual puzzle-adventure title and uses AI assistants to speed up crash/log analysis and produce clearer test cases and bug reports.”
Tanushree Kakad
Intern Software Engineer specializing in AI, computer vision, and VR
“Robotics software engineer with hands-on experience integrating vision-based perception with control logic in ROS simulation environments. Focused on debugging real-time timing/data-flow issues, improving system stability through incremental scenario testing in Gazebo, and supporting reliable deployments with Docker and basic CI/CD automation.”
“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.”