Ruthvika

Key Skills

Software

Don't disclose

Other

Top Subject Matter

Machine Learning model training and release (computer vision architectures)

LLM/RAG pipeline deployment

AI-enabled analytics

Top Data Types

3D Sensor

Image

Text

Document

Top Task Types

Data Collection

Function Calling

Prompt + Response Writing (SFT)

Freelancer Overview

Machine Learning Engineer | Tech Mahindra | Google Keras Hub. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose, Other, and AWS (S3. Education includes Master of Science, California State University, Sacramento (2026) and Bachelor of Technology, R.M.D. Engineering College. AI-training focus includes data types such as Computer Code, Programming, and 3D Sensor and labeling workflows including Data Collection, Function Calling, and Prompt + Response Writing (SFT).

Labeling Experience

Founder & CEO – ARCH.AI | AI Product Studio

OtherPrompt + Response Writing (SFT)

Founded and deployed an interior design AI product from prototype to production using NVIDIA NIM APIs and vector similarity search. Designed and iterated a multimodal RAG architecture that supports user room photo uploads and cultural preference inputs. Built toward scalable AI product behavior driven by user feedback and expanded cultural design categories. • Shipped a production application using NVIDIA NIM APIs (Nemotron-70B, Llama Vision, Flux) and Pinecone • Implemented multimodal RAG for room photos and cultural preference inputs • Iterated on user feedback to improve outputs and expand supported categories • Developed toward a scalable product experience based on retrieval-augmented generation

2026 - Present

Forward Deployed Engineer | California State University, Sacramento

OtherFunction Calling

Owned the end-to-end deployment of a production RAG pipeline and an LLM-powered IT support platform, translating stakeholder needs into working AI capabilities. Embedded with non-technical stakeholders across multiple departments to operationalize ETL pipelines, data ingestion workflows, and ML-powered analytics dashboards. Performed on-site root-cause analysis and remediation for a misclassification issue affecting compliance data, supporting reliable AI-assisted outputs in production. • Implemented and supported a production RAG pipeline and LLM support system • Translated business problems into AI-enabled technical workflows and analytics • Conducted root-cause analysis to fix misclassified compliance data impacting multiple colleges • Built enterprise integrations (Microsoft Copilot Studio, ServiceNow) with defined connector contracts and escalation workflows

2025 - Present

Software Developer Intern | California Department of Conservation

3D SensorData Collection

Deployed and maintained production AWS data pipelines ingesting live seismic sensor data for downstream analytics and real-time processing. Embedded with geoscientists and regulatory program managers to convert ambiguous stakeholder requirements into technical specifications and iterative solutions. Built full-stack real-time analytics features using Python, JavaScript, D3.js, ArcGIS, and REST APIs, delivering production-ready functionality under zero-downtime constraints. • Ingested 10+ GB/day of seismic sensor data from 60+ remote stations into AWS pipelines • Translated domain expert workflows into technical specifications for data ingestion and analytics • Shipped production full-stack real-time analytics features using REST APIs • Optimized distributed query performance via profiling, schema analysis, and caching

2024 - Present

Machine Learning Engineer | Tech Mahindra | Google Keras Hub

Don't discloseData Collection

Contributed DenseNet, CSPNet, and DeepLabV3 work to Google’s Keras Hub, which involved preparing and working with large-scale training datasets and model releases. Resolved production issues across TensorFlow and Keras while shipping improvements to a global developer community. Supported machine learning development workflows that function as AI training and model refinement activities for published models. • Trained models on large-scale datasets and released pre-trained weights • Debugged production bugs in TensorFlow/Keras • Supported upstream contributions for an external ML developer community • Delivered improvements aligned to public model distribution

2023 - 2023

Education

Work History