Shreyansh Jain

AI Researcher

Bengaluru, Karnataka, India1 yr 8 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in developing secure AI systems and LLM guardrails.
Proven track record in business process automation.
Strong background in LiDAR technology and vehicle detection.

Stackforce AI infers this person is a specialist in AI Security and Business Process Automation within the AI and Transportation industries.

Contact

sj.shreyanshjain2002@gmail.com LinkedIn

Skills

Core Skills

Ai SecurityBusiness Process AutomationComputer VisionMachine Learning

Other Skills

C++Choice ModelingData WranglingDataikuDeep LearningDockerExtract, Transform, Load (ETL)FastAPIKalman FilterLangChainLangGraphLanggraphLiDARML AlgorithmsNVIDIA Nemoguardrails

About

I design and deploy secure AI systems with a focus on LLMs, multi-agent architectures, and AI security. I built tools for business process automation, guardrail implementation, and customer support use cases, ensuring AI solutions are both innovative and compliant. Previously, I collaborated with Hiroshima University’s Infrastructure Planning Lab, developing LiDAR-based models for real-time vehicle detection, lane tracking, and travel behavior prediction using point-cloud datasets. My interests span classical ML, agentic systems, and AI safety. I enjoy tackling Kaggle challenges and exploring emerging AI trends. Open to discussions on AI/ML, collaborative projects, or shared learning!

Experience

Goldman sachs

Analyst - AI Engineer

Sep 2025 – Present · 6 mos · Bengaluru, Karnataka, India

Deloitte

Analyst - AI Engineer

Jul 2024 – Sep 2025 · 1 yr 2 mos · Bengaluru, Karnataka, India · Hybrid

Developed secure and scalable LLM guardrails using NVIDIA Nemoguardrails, FastAPI, and Docker. Engineered automation tools with LangGraph and RAG to streamline business processes, reducing documentation time by 80%. Built RBAC systems for 300+ users and automated financial reconciliation pipelines (Python/Dataiku), processing 100k+ records/hour. Delivered production-ready AI solutions balancing compliance, efficiency, and innovation.

NVIDIA NemoguardrailsFastAPIDockerLangGraphRAGPython+3

Hiroshima university

Research Intern

May 2023 – Jul 2023 · 2 mos · Roorkee, Uttarakhand, India · Remote

Developed computational graph-based discrete choice models to test the spatial transferability of mode choice using actual data based on Hiroshima prefecture, Japan.
Conducted a comparative study to assess the effectiveness of various model formulations, and optimization methods and accessed the model based on results from classical choice models.
Performed model fine-tuning via nested cross-validation and Bayesian optimization.

Indian institute of technology, roorkee

Research Intern

Jun 2022 – Apr 2023 · 10 mos · Roorkee, Uttarakhand, India · On-site

Built an ML pipeline for dynamic and sparse LiDAR point cloud-based vehicle detection, classification, and tracking. Adapted ML algorithms such as RANSAC and DBSCAN to suit sparse point cloud data to enhance vehicle detection. Designed an unscented Kalman Filter to facilitate vehicle tracking and classification, enhancing overall performance.