Devendra k
senior artificial intelligence and machine learning engineer
Navi Mumbai
4+ years of work experience
Oct 20224 yrs 1 moPresent
Banglore
20224 yrs 10 mosPresent
1. Designed and implemented enterprise-scale RAG pipelines enabling semantic search across large document repositories, improving retrieval accuracy by over 40% and reducing average query response time by 60%.
1. Built and deployed scalable ML microservices using FastAPI and Docker, orchestrated via Kubernetes to support high-availability systems handling 10,000+ daily requests with 99.9% uptime SLA.
1. Developed end-to-end MLOps pipelines using MLflow and AWS SageMaker to automate model tracking, versioning, and deployment, reducing release cycles by 35% and eliminating manual handoffs.
1. Optimized LLM inference performance and cost by 45% through prompt engineering, token optimization, quantization, and intelligent caching strategies, saving ~$120K annually in cloud compute costs.
1. Led architectural decisions for a multi-modal AI platform, evaluating and integrating state-of-the-art foundation models (GPT-4, Claude, Llama 2) based on cost-accuracy-latency trade-offs.
1. Implemented model monitoring and automated drift detection systems, reducing model degradation incidents by 70% and enabling proactive retraining triggers.
1. Conducted code reviews, established engineering best practices, and mentored 4 junior engineers, improving team velocity by 25% through structured onboarding and pair programming sessions.
1. Collaborated with product, data, and business stakeholders to integrate AI capabilities into core workflows, delivering measurable ROI and improved operational efficiency.
20193 yrs2022
1. Developed and deployed advanced NLP solutions including sentiment analysis, text summarization, named entity recognition, and question-answering systems achieving 20–30% performance improvement over baselines.
1. Fine-tuned pre-trained language models (BERT, RoBERTa) using domain-specific corpora, boosting downstream task accuracy by up to 18% with LoRA-based parameter-efficient techniques.
1. Engineered computer vision pipelines for automated image classification and video object detection using TensorFlow and PyTorch, processing 1M+ images/month with 94% precision.
1. Automated machine learning workflows using AWS Lambda and S3, reducing manual intervention by 80% and improving end-to-end processing efficiency by 50%.
1. Built reusable data processing and feature engineering modules, cutting new project onboarding time by 40% and ensuring consistent data quality across pipelines.
1. Conducted rigorous model evaluation, hyperparameter tuning, and ablation studies, documenting findings in internal knowledge bases adopted as team standards.
1. Partnered with data engineering teams to design scalable feature stores, enabling rapid experimentation and reducing feature pipeline duplication across 6 ML projects.
20172 yrs2019
1. Designed and implemented collaborative filtering and content-based recommendation systems, increasing client platform engagement by 22% and directly contributing to revenue growth.
1. Built time-series forecasting models using ARIMA and LSTM networks for demand prediction, achieving MAPE below 8% across multiple retail clients.
1. Automated ETL pipelines using Python and Apache Airflow, handling 5TB+ of daily data ingestion with robust error handling and alerting, ensuring 99.5% pipeline reliability.
1. Developed interactive dashboards and visualization tools using Plotly and Tableau, enabling non-technical stakeholders to self-serve model insights and track KPIs in real time.
1. Collaborated with business teams to define AI problem scopes, translating ambiguous requirements into structured ML solutions with measurable success criteria.
Devendra’s AI Stack
Education
High School Diploma
Margadarshi Society
High School Diploma
narayana junior college
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