Amith Penumudi

Software Engineer

Bengaluru, Karnataka, India1 yr 6 mos experience

Key Highlights

  • Developed scalable call-processing tools improving system reliability.
  • Built a GPT-style Transformer for text generation.
  • Created ML models for accurate climate predictions.
Stackforce AI infers this person is a Data Scientist with strong software engineering skills in the Climate Tech and SAAS sectors.

Contact

Skills

Core Skills

MicroservicesCi/cdMachine LearningData Science

Other Skills

LensGitHubExploratory Data AnalysisTransformersDeep Neural Networks (DNN)Long Short-term Memory (LSTM)Random ForestTensorFlowConvolutional Neural Networks (CNN)GitGardenJavaHTMLCascading Style Sheets (CSS)JavaScript

About

I am a results-driven professional with a strong foundation in software engineering, having built reliable, scalable, and production-ready systems. My experience includes developing robust backend and full-stack tools, improving system stability, optimizing workflows, and addressing InfoSec challenges in fast-paced, enterprise environments. Building on this foundation, I have developed expertise in data science and machine learning. I have worked on predictive modeling, deep learning, and transformer-based architectures, applying them to real-world problems such as weather forecasting and financial time series analysis. My experience spans the complete ML workflow—data preprocessing, feature engineering, model training, evaluation, and deployment—while leveraging software engineering best practices to ensure scalable and maintainable solutions. Key Skills & Technologies • Python | Java | C++ | C | JavaScript | SQL • Machine Learning | Deep Learning | Transformers | Time Series | Data Analysis & Visualization | AI • Docker | Kubernetes | Microservices | • CI/CD | GitHub Actions | Datadog | DBMS Impact & Experience Highlights • Developed scalable call-processing and observability tools at Uniphore, improving system reliability, stability, and monitoring while resolving critical InfoSec issues. • Built and evaluated machine learning and deep learning models at Jio to predict temperature and heatwave occurrence, leveraging regression, classification, and feature engineering on large-scale climate data. • Built a GPT-style Transformer from scratch (11M parameters) to generate Shakespeare-style text, implementing multi-head attention, positional embeddings, and an optimized GPU-accelerated training pipeline. • Built ML/DL models to classify swing points in stock prices, engineered features from price movements, handled class imbalance, and post-processed predictions for accurate results. Feel free to reach out if you’d like to discuss data analytics, data science, machine learning , ai or potential collaboration: amithpenumudi@gmail.com

Experience

1 yr 6 mos
Total Experience
1 yr 3 mos
Average Tenure
2 mos
Current Experience

Target

Engineer

Apr 2026Present · 2 mos · Bengaluru, Karnataka, India · Hybrid

Uniphore

Software Engineer

Jun 2024Oct 2025 · 1 yr 4 mos · Chennai, Tamil Nadu, India · Hybrid

  • Built an integration testing framework adopted across 3 microservices, enabling realistic end-to-end validation of voice-processing workflows and supporting 200+ concurrent simulated call sessions.
  • Automated REST session orchestration, media streaming validation, and metadata verification, reducing manual QA effort by 40% and significantly lowering regression escape incidents.
  • Integrated the testing framework into GitHub Actions CI/CD, enabling automated regression checks and cutting test time by 60%, which accelerated feedback loops and improved release quality.
  • Built an internal call-control utility replicating agent workflows (hold, transfer, conference), reducing onboarding and troubleshooting workload for support teams by 35%.
  • Implemented dynamic token-based request handling to support multiple data extraction scenarios across services, improving extensibility and reducing code duplication.
  • Designed and published metrics to Datadog, tracking requests and responses across multiple services for enhanced monitoring and observability.
  • Improved service stability by refactoring critical components and adding deterministic timeout and retry strategies, contributing to zero-downtime deployments.
  • Resolved critical bugs across backend services, improving system reliability and preventing recurring issues.
LensGitHubMicroservicesCI/CD

Jio platforms limited (jpl)

Data Scientist

May 2023Jul 2023 · 2 mos · Bengaluru, Karnataka, India · On-site

  • Built machine learning models that accurately forecasted temperature and heatwaves up to 5 days in advance, achieving top performance with Random Forest.
  • Processed and engineered features from decades of historical weather data (Kaggle, ERA5), including temporal transformations, standardisation, and hyperparameter tuning.
  • Trained multiple machine learning and deep learning models for both regression and classification tasks.
  • Evaluated model reliability using MAE, R², accuracy, and F1-score, optimizing performance through model validation and tuning strategies.
  • Gained hands-on experience in ML workflows, feature engineering, and real-world climate data applications, converting complex datasets into actionable predictions.
Exploratory Data AnalysisMachine LearningData Science

Education

National Institute of Technology Karnataka

Bachelor's degree — Computer Science

Dec 2020Apr 2024

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