Help & Supportcareers@gravityer.com
Entry-level AI Engineer with Python and Machine Learning expertise
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Fresher aspiring to build a career in AI/ML and Data Science. Skilled in Python, SQL, and Machine Learning, with a passion for solving problems and working with data. Eager to learn and contribute to real-world projects.
Dharmsinh Desai University
BTech · Information Technology
August 1, 2023 – June 30, 2027
Oxford School of Science
12th Science · Science
June 1, 2021 – May 31, 2023
VisualTalk – Real-time Sign Language Translator
June 1, 2025 – Present
Currently developing an end-to-end ASL-to-text conversion system to facilitate real-time communication for deaf and hard-of-hearing users. Engineering a data pipeline to categorize 36 distinct gesture classes using MediaPipe for precise hand landmark detection and tracking. Refining deep learning model performance within Jupyter Notebook, focusing on enhancing classification accuracy through iterative dataset augmentation.
Customer Churn Prediction MLOps Pipeline
June 1, 2025 – Present
Developed a machine learning model to predict customer churn using historical customer behavior data. Implemented experiment tracking, model versioning, and performance monitoring using MLflow. Built REST APIs with FastAPI to serve real-time predictions and enable seamless model integration. Containerized the application using Docker and automated testing and deployment through GitHub Actions.
ChatLED – WhatsApp-Based IoT Home Automation
June 1, 2025 – Present
Developed a low-cost home automation system allowing users to remotely control and monitor lighting via WhatsApp messaging. Integrated Twilio API and ThingESP cloud services to bridge communication between mobile messaging and hardware. Engineered firmware in C++ for NodeMCU (ESP8266) to process real-time commands such as “LED ON/OFF" and provide instant status feedback. Designed a scalable circuit architecture using breadboarding and resistors, with planned expansion for appliance control using relay modules.
Cultural Fit Analysis
The candidate's academic projects demonstrate a diverse range of interests, from IoT home automation to real-time sign language translation and MLOps. This breadth of engagement suggests adaptability and a willingness to explore different technical domains. The focus on practical application and problem-solving aligns well with an innovative engineering culture. However, as a fresher, there is no direct evidence of collaboration in a professional team setting, which is a key aspect of cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an eagerness to learn and apply new technologies. The 'VisualTalk' project, in particular, suggests an interest in developing solutions with social impact. The MLOps project shows an understanding of development best practices like containerization and CI/CD, which are crucial for operational fit in a modern engineering team. However, without direct work experience or psychometric test results, it's difficult to assess communication, stress handling, or team collaboration skills.