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LOCAL_INFERENCE / AGENT_HARNESS / FAILURE_RECOVERY AI/ML Engineer building edge AI systems and tool-using agents AI/ML internships | agent systems | edge inference | 1 patents published |
Important
Actively looking for AI/ML internship roles where edge inference, tool-using agents, and industrial data matter more than demo-only chatbots.
| patents 1 published |
scale 5,000 machines |
edge <100ms inference |
agents recovery pipelines |
[profile]
name = "Anshul Panigrahi"
role = "AI/ML Engineering Intern"
location = "VIT Vellore, Tamil Nadu, India"
current_build = "Hermes Agent + custom tool harness"
[operating_rules]
cloud = "optional"
failure = "recover, verify, hand off"
target = "edge AI, industrial ML, embedded inference"| Track | Repositories |
|---|---|
| Flagship AI/ML | Predictive Maintenance (private/on request) · Mode Discovery · Stella · Veri-Dose |
| Agents + Systems | Cognitive Load Scheduler · Aether Dashboard |
| Edge + IoT | Vision Air Sim · Air Safety Assistant · Smart Energy |
| Vision + Security | Face Privacy Filter · Sobel CUDA · QR Security · SecureTorrent |
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Real-Time Predictive Maintenance Kafka, Spark, Cassandra, PyTorch, and graph analytics across 5,000 simulated factory machines to predict cascade failures before downtime.
Repository available on request. |
Physical-Bounded Multimodal Mode Discovery Unsupervised fault discovery on NASA CMAPSS and CWRU. HDBSCAN proposes regimes; physics constraints reject invalid vibration and thermodynamic behavior.
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Stella On-device health assistant with Mistral 7B via Ollama. Wearable anomalies become local context, keeping personal health queries off the cloud.
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Veri-Dose Smart medication dispenser using quantized MobileNetV2 on Raspberry Pi 4. Low-confidence predictions route to a human fallback.
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I am not building chatbots. I am building systems where models plan, call tools, recover from failure, and hand off when another model or tool is a better fit.
open agent harness
The model is not the product. The harness is: context routing, tool contracts, verification, recovery policy, and handoff logic.
flowchart LR
A["input"] --> B["context router"]
B --> C["planner model"]
C --> D["tool call"]
D --> E{"verified?"}
E -->|yes| F["ship action"]
E -->|no| G["recover"]
G --> H{"specialist needed?"}
H -->|yes| I["sub-agent"]
H -->|no| C
I --> F
Current stack: N8N, Claude Code, OpenAI Codex, Cursor Agent SDK, OpenClaw, Hermes, and custom tool pipelines when frameworks get in the way.
| Certification | Issuer | Date |
|---|---|---|
| Getting Started with Deep Learning | NVIDIA DLI | Mar 2026 |
| OCI 2025 AI Foundations Associate | Oracle | Mar 2026 |
| Software Engineer Intern Certificate | HackerRank | Feb 2026 |
| Intro to Machine Learning | Kaggle | Feb 2026 |