About tian
I am an Applied ML Engineer dedicated to bridging the gap between advanced machine learning and physical automation. After 6+ years of architecting complex engineering breakthroughs and scaling infrastructure at Princeton, my focus is entirely product-driven. I am actively transitioning to industry to apply my background in GPU optimization, real-time vision language model, and agentic workflow orchestration to drive immediate business value in fast-paced production environments.Currently, I lead the development of production-grade, real-time vision-language agent systems at Princeton, where I was promoted to scale our intelligent control platforms. My work specializes in deploying low-latency AI pipelines on edge hardware, designing stateful perception-to-action frameworks, and building scalable multi-device infrastructure. By converting complex physical workflows into autonomous, data-driven operations, I build systems optimized for high-reliability deployments, multi-tenant usage, and automated operations.Core ExpertiseAI & Agentic Systems: Vision-Language Models (VLMs), Local LLMs (8B to 70B parameters), QLoRA Fine-Tuning, Multi-Level Reasoning Agents.Real-Time Computer Vision: High-Throughput Object Tracking Pipelines (~100MB/s, YOLO, CNN), Sub-50ms Low-Latency Inference, Edge GPU Deployment (RTX 4090 / H200).Control Systems Architecture: Closed-Loop Control, Memory-Augmented Systems (RAG), Stateful Perception-to-Action Frameworks, Distributed Compute.Product & Infrastructure: Web-Based Production Platforms, Multi-Device Orchestration, Centralized Scheduling, Real-Time Inference Routing.Selected Impact HighlightsAccelerated Throughput: Replaced manual scanning with AI-guided adaptive sampling, boosting data acquisition throughput by 29×.Scale & Adoption: Deployed a centralized autonomous imaging platform supporting 80+ concurrent active users and multiple cross-functional engineering teams.
Key Skills
Experience
Applied Ml Engineer
CurrentPrinceton University
* Boosted Data Efficiency: Improved data collection throughput by 29× by replacing manual scanning with AI-guided adaptive sampling strategies. * Led Production Deployment: Spearheaded end-to-end launch of a web-based autonomous optical platform serving 80+ internal users across 19 teams. * Optimized Real-Time CV: Developed Python computer vision pipelines on NVIDIA RTX 4090 edge GPUs, hitting sub-50ms latency at 100MB/s data rates. * Architected Multi-Stage Agents: Built LangGraph AI agents using local 8B and H200-hosted 70B models for natural-language experiment control. * Built Robust Infrastructure: Containerized AI services via Docker across 10 autonomous systems with structured logging and fail-safe protections. * Managed Release Cycles: Controlled system reliability using Git-based pull requests, staged rollouts, and rollback strategies. * Trained Custom Models: Designed PyTorch CV models for tracking and fine-tuned LLM agents using QLoRA, prompting, and RAG pipelines. * Enabled Closed-Loop Control: Linked live model inference directly with hardware actuation and integrated Langchain for RAG workflows.
Automation & Computer Vision Engineer
Princeton University
* Designed and built high-precision instrumentation for 3D single-particle tracking, managing multi-gigabyte real-time datasets. * Developed statistically rigorous frameworks using Maximum Likelihood Estimation (MLE) to characterize signal dynamics in high-noise environments. * Implemented custom signal processing algorithms (SVD, FDTD) to reconstruct ultrafast physical features with sub-millisecond latency. * Built the foundational data architecture for the lab, transitioning manual data collection into a structured, machine-learning-ready database.
Education
Penn State University
Doctorates
Beihang University
Bachelors
Interested in connecting with tian?
Sign up for NinjaHire to send a connection request.
Common Questions
What is tian's expertise?
tian specializes in Fine-Tuning Engineer, with expertise in agentic workflows, algorithms, artificial intelligence, attention to detail, autonomous systems.
Where is tian located?
tian is based in princeton junction, new jersey, united states.
How much experience does tian have?
tian has 7+ years of professional experience.
How can I contact tian?
You can connect with tian through NinjaHire by signing up for a free account.
Other Fine-Tuning Engineers
Looking for a different Fine-Tuning Engineer?
Describe exactly who you need and NinjaHire will source them for you.
Type a role to try NinjaHire for free