Help & Supportcareers@gravityer.com
ML Engineer with 3+ years in machine learning, deep learning, and computer vision automation.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer with 2 years of experience specializing in machine learning, deep learning, LLM evaluation, and computer vision automation. Skilled in building scalable ML pipelines, optimizing model performance, and deploying Al-driven solutions. Hands-on experience with TensorFlow, PyTorch, LLMs (LLAVA, Gemma, Mistral), and production-oriented ML workflows. Strong ability to transform real-world problems into deployable Al systems with measurable impact.
SASTRA University
M.Sc. · Data Science
N/A – June 30, 2022
SASTRA University
B.SC. · Electronics & Computer Science
N/A – June 30, 2020
Sundar Infographic Analytics, @SNC
Machine Learning Engineer
September 1, 2025 – Present
Chennai, Tamil Nadu, India
SEEWISE.AI
Machine Learning Data Associate
March 1, 2024 – September 1, 2025
Chennai, Tamil Nadu, India
Pixstone images pvt ltd
Data Coordinator
September 1, 2022 – November 1, 2023
Chennai, Tamil Nadu, India
Leaf disease detection using Deep Learning techniques
June 1, 2026 – Present
Built a deep learning model with Conditional GAN and Densenet121, achieving high accuracy in leaf disease detection for early diagnosis.
Image recognition of four rice leaf disease detection based on deep learning and SVM
June 1, 2026 – Present
Achieved 96% accuracy with CGAN and Densenet121 for early leaf disease detection, reducing crop loss
Certification in DATA ANALYTICS
Greens Technologies
June 1, 2026 – Present
Certification in AWS & Devops
Login360
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from academic deep learning projects to industry roles in ML engineering and data coordination, suggests adaptability. The current role as an ML Engineer aligns well with the target role, indicating a clear career path. The breadth of skills across ML, DL, LLMs, Computer Vision, and MLOps indicates a proactive approach to learning and development, which is a positive cultural fit for dynamic tech environments. However, the lack of community involvement or open-source contributions limits a full assessment of cultural fit.
Soft Skills & Operational Fit
The candidate's experience descriptions indicate collaboration with engineering teams and cross-functional stakeholders, suggesting an ability to work in a team environment. The focus on reproducible ML experiments and model optimization points to an operational mindset. However, without specific behavioral assessment data, a deeper evaluation of soft skills like problem-solving under pressure or conflict resolution is not possible.