Vineeth CR

AI Researcher

Boston, Massachusetts, United States11 yrs 11 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Developed scalable AI solutions for cybersecurity.
Expert in anomaly detection and fraud prevention.
Proven track record in optimizing AI model performance.

Stackforce AI infers this person is a Cybersecurity and AI/ML specialist with a focus on scalable solutions.

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Skills

Core Skills

Fraud DetectionAnomaly DetectionAnalyticsDeep Learning

Other Skills

AerodynamicsAlgorithmsAmazon Web Services (AWS)AutomationCCAECFDComputer VisionConvolutional Neural Networks (CNN)Cyber DefenseCyber Threat Hunting (CTH)DashboardsData AnalysisData PipelineData Visualization

About

I develop cloud-native AI/ML applications for threat detection and fraud prevention. My core domain expertise lies in cybersecurity (HTTP layer). I've built: - Secure AI agents - Enabled LLM-driven automation - Designed and secured AWS S3 data lakes - ETL pipelines for forecasting models - Deep Learning models for anomaly detection - Conducted statistical A/B tests Skill-set: ● Languages &Frameworks: Python, Java, JavaScript, TypeScript, Node.js, SQL ● Data & AI/ML Tools: Langchain, Pytorch, Tensorflow, Apache Airflow, DataRobot, Vector stores, Embeddings, LLM API orchestration, MCP-tool calling, HuggingFace Transformers, Pydantic-AI, AWS Sagemaker ● CI/CD & DevOps: Jenkins, GitHub Actions, GitLab CI, Infrastructure as Code (Terraform, CloudFormation) ● Security & Validation: OAuth2, JWT, API abuse detection, WAF, DAST (Burp Suite) ● Infrastructure & Cloud: Kubernetes, Docker, Kafka, AWS, GCP ● Databases & Analytics: Elasticsearch, Postgres, SQLServer, AWS Quicksight, Prometheus, Grafana, DataDog Lastly, I explored tensor factorization to compress wide neural networks at Purdue and I've 6 years of experience developing applications for energy, automotive and aerospace industries.

Experience

11 yrs 11 mos

Total Experience

2 yrs 11 mos

Average Tenure

Current Experience

Cequence security

Machine Learning Engineer

Dec 2018 – Aug 2025 · 6 yrs 8 mos

Joined as part of the early Series A team that architected a scalable, event-driven API Security Platform leveraging Java, Kafka, and Kubernetes
Enabled developers to build secure AI agents that can consume enterprise APIs over Model Context Protocol (MCP)
Built and scaled ML anomaly detection pipelines using Ensemble Tree and Deep Learning models, reducing human intervention.
Developed ETL pipelines to train, on a schedule, multiple forecasting models that predict browsers request rate with an average SMAPE score of 25%
Enabled junior technical staff to take on more complex projects through continuous support

Fraud DetectionAnomaly DetectionAnalyticsPrompt EngineeringDebuggingPython+7

Insight data science

AI Fellow

Jan 2018 – Jan 2018 · 0 mo · San Francisco Bay Area

Developed a deep learning–based object detection pipeline using Keras, TensorFlow, and YOLOv2 to classify recyclable materials (metal, plastic, glass, cardboard) from images, achieving a mean average precision (mAP) of 0.84 in real-time inference.
Optimized AI model serving infrastructure by converting Keras models to TensorFlow frozen graphs and ﬁne-tuning GPU performance on NVIDIA Tesla K80, reducing inference latency to 0.06s per image.
Curated custom datasets (≈ 170 labeled images per class) and engineered anchor box conﬁgurations and loss functions, improving model generalization across variable lighting and orientations.

Anomaly DetectionAnalyticsDebuggingPythonAmazon Web Services (AWS)Dashboards+4

Purdue university

Graduate Research Assistant

May 2017 – Aug 2017 · 3 mos · West Lafayette

Designed an efficient data pipeline to analyze climate, socio-economic and electricity data of 8 most energy intensive states in USA
Innovative categorization of user behavior, based on intensity of electricity consumption
w.r.t climate, improved the ensemble tree model's predictive power by more than 30%

RAnalyticsDebuggingPythonData VisualizationConvolutional Neural Networks (CNN)

Siemens plm software

Senior Engineer

Jan 2012 – Jan 2015 · 3 yrs · Greater Chennai Area

As a global team member, I developed scalable models for automotive/energy industries.
Developed Python automation plugins and APIs in Simcenter Amesim, enabling reproducible simulation scripting and workﬂow orchestration that reduced setup time by 40%+
Led optimization strategy consulting using ML optimization algorithms such as Genetic Algorithm and NLPQL, reducing hyper-parameter tuning cycles by 2x.
Led a team that consulted with a supplier in delivering production-ready code to an OEM.
Mentored interns on simulation workﬂows and model development, ensuring eﬃcient knowledge transfer.

AnalyticsDebuggingPythonDashboardsData VisualizationShell Scripting

Idea research

Associate

Jan 2009 – Jan 2011 · 2 yrs

At this consulting start-up, I built rapid-prototyping tools that simulated flight mechanics in Python/Matlab/C. For instance,
Developed modular real-time (RTOS) software for executing flight algorithms on NI-PXI hardware, enabling efficient testing and validation of embedded flight controllers.
Collaborated with cross-functional teams to develop a Particle Swarm Optimization–based tool that halved design iteration cycles
Implemented a novel feature(Boron particle combustion) for a C code that simulates ramjet engine combustion

CAnalyticsDebuggingPythonData Visualization