Aryan Raj
Software Engineer (AI/ML) at ValueLabs
Building deep learning solutions, generative AI products, and data infrastructure at scale.
View ResumeBuilding AI Solutions that Matter
I am a Machine Learning Engineer and Backend Developer with experience building practical AI solutions and scalable applications. I graduated in Computer Science and Engineering from SRM Institute of Science and Technology, with hands-on work in deep learning, generative AI, and cloud-based services.
I am currently working at ValueLabs on building scalable AI solutions to drive growth. In my current role, I work on building AI/ML solutions and contributing to developer tooling and analytics infrastructure. I've worked on autonomous AI agents, prompt engineering frameworks, and scalable machine learning systems that reduce manual effort and improve performance.
My internship experience spans AI-driven identity and fraud detection, serverless backend development, and research in machine learning systems for autonomous perception. I have also developed full-stack AI-based platforms that combine semantic search, OCR, and real-time inference.
I enjoy working on projects that solve real problems through practical application of AI and backend technologies, with a focus on clean design and measurable impact.
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Schedule on Cal.comWork
- Architecting and delivering enterprise-scale generative AI solutions, including ValueLabs' flagship AiDE Conversational Insights, using advanced multi-agent architectures to generate scalable insights and support enterprise deployments.
- Designing and implementing modern data platforms—including data warehouses, lakehouse architectures, and schema-level migration strategies—to enable scalable analytics and organization-wide KPI reporting.
- Building and integrating internal AI-powered productivity tools, including a company-wide intelligent search platform, to streamline developer workflows, accelerate knowledge discovery, and reduce software licensing costs by 50%.
- Building and deploying autonomous AI agents to automate complex SEO workflows and content analysis pipelines, reducing manual effort by 60% and improving turnaround times.
- Designing and implementing scalable machine learning infrastructure to support multi-step reasoning and real-time content optimization.
- Architecting prompt engineering frameworks and evaluation systems to ensure high-quality, contextually relevant SEO recommendations across diverse client domains.
- Developed and fine-tuned LLM-based solutions to automate KYC and fraud detection workflows, tailored for real-world, domain-specific regulatory use cases across financial institutions.
- Led evaluation and benchmarking of LLMs on over a million real-world data points, setting up scalable performance monitoring pipelines and achieving industry-accepted False Acceptance Rate (FAR) and False Rejection Rate (FRR) thresholds.
- Optimized and deployed state-of-the-art computer vision and NLP models for identity verification, significantly improving inference speed and accuracy under production constraints.
- Engineered and deployed AI solutions leveraging the AWS ecosystem with a focus on Generative AI to build scalable, client-centric applications.
- Developed and maintained 10+ Generative AI-based microservices with industry-standard integrations using AWS Lambda, API Gateway, and OpenTelemetry for observability.
- Architected scalable, serverless backends to support efficient retrieval and generation workflows across diverse application domains.
- Collaborated with the Department of Ocean Engineering to design and implement a machine learning-based anti-collision system, improving accuracy of existing solutions by over 28%.
- Developed marine object detection, tracking, and localisation systems using stereo vision-based camera setups for alternative navigation in unmanned surface vehicles (USVs).
- Worked with state-of-the-art computer vision models and successfully deployed the solution on edge-based IoT hardware for real-time maritime applications.
Education
B.Tech Computer Science and Engineering with spl. in Artificial Intelligence and Machine Learning
High School, CBSE (X and XII) Non Medical Sciences (With Computer Science and Commercial Arts)
Projects
PaperPilot
- Built a full-stack AI-powered research assistant platform for semantic search and summarization of academic papers with high precision retrieval.
- Implemented advanced RAG pipelines using Pinecone for vector storage and Jina AI embeddings, enabling context-aware paper discovery.
- Developed a Next.js frontend with TailwindCSS and a Flask backend, processing over 500+ papers with structured metadata extraction and citation analysis.
- Built a full-stack AI-powered research assistant platform for semantic search and summarization of academic papers with high precision retrieval.
- Implemented advanced RAG pipelines using Pinecone for vector storage and Jina AI embeddings, enabling context-aware paper discovery.
- Developed a Next.js frontend with TailwindCSS and a Flask backend, processing over 500+ papers with structured metadata extraction and citation analysis.
Engineering
Languages
C, C++, Python, Java, JavaScript, SQL (Postgres), HTML, CSS, R
Frameworks
React.js, Next.js, Node.js, Flask, FastAPI, TailwindCSS, JUnit, Material-UI
Machine Learning
NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, OpenCV, NLP, LangChain, LangGraph, Llama-Index, Transformers, HuggingFace
Developer Tools
Git, Docker, Kubernetes, AWS, Azure, Google Cloud Platform, CDK, Terraform, Redis, Pinecone
Astitva Veer Garg, Aryan Raj, Dr. Anitha D
Springer Nature · Lecture Notes in Networks and Systems, vol 1652 · October 31, 2025
- *Secured 1st place at the Standard Chartered Hackathon for developing OpenKYC, an innovative KYC solution that streamlined identity verification processes.
- *Won 2nd place at Hack Nova 2024 with Educative.AI, an educational technology project later selected to represent at Innverve 2023, Army Institute of Technology (AIT), Pune.
- *Received the Best Project Award in the Open Innovation category at MLH Meso Hack 2022 for the project AI-Roadguard.
- *Authored technical articles on AI for prestigious Medium journals, including the DataX Journal.
- Dify · Open Source Contributor
Contributed to various open-source projects; notable contribution includes Dify, a project with over 100,000 stars on GitHub.
- Next Tech Lab · Research Member · 2021-2025
Conducted research as a member of Norman and McCarthy Labs, collaborating on web and machine learning projects, specializing in deep learning for image-related tasks.
- Data Science Community SRM · Technical Director · 2022-2023
Organized technical events, workshops, and hackathons including DS Hack 2.0.
- SRM Quantum Computing Club · ML Lead
Led machine learning initiatives, managing projects at the intersection of quantum computing and machine learning.
- SRMKzilla · Event Domain Member
Served as Event Domain Member of SRMKzilla, the official Mozilla club on campus, promoting community contributions and engagement.