Hi, I'm Taaran Jain
I build intelligent systems — from fine-tuned LLMs and RAG pipelines to computer vision models and end-to-end ML platforms. Turning data into decisions, and research into real-world products.
01 / About
About Me
I'm obsessed with making machines learn — and making sure what they learn is actually useful.
Hey! I'm Taaran, an AI Engineer passionate about building systems at the intersection of large language models, deep learning, and real-world applications.
I work across the full ML lifecycle — from exploratory data analysis and model research to serving models at scale in production. My current focus is on LLM-powered applications: retrieval-augmented generation (RAG), agentic AI, and multimodal systems.
When I'm not training models or writing code, I'm reading the latest papers on arXiv, contributing to open-source AI tools, or experimenting with new architectures.
2+
Years in AI/ML
5+
Projects Deployed
2+
Papers Published
10+
GitHub Repositories
LLM Engineering
Building RAG pipelines, fine-tuning transformers, and deploying production-grade LLM applications.
Data Science
End-to-end ML pipelines — from raw data ingestion and feature engineering to model evaluation.
MLOps & Deployment
Taking models from notebook to production with robust CI/CD, monitoring, and scalability.
Research-Driven
Staying close to SOTA research and translating cutting-edge ideas into practical systems.
02 / Experience
Work Experience
My journey through AI engineering, ML research, and production deployment.
AI Engineer
e-Marketing.io
Sole AI Engineer responsible for designing and shipping the full suite of AI-powered products for a performance marketing agency and its clients — owning everything from problem scoping and model selection to deployment and iteration.
- ▸Built an AI Meeting Summarizer that converts hour-long recordings into structured briefs with decisions and action items — saving teams hours of follow-up every week.
- ▸Developed a Keyword Analysis Engine that replaced gut-feel content decisions with NLP-driven insights on trends, intent, and competitor gaps.
- ▸Shipped AI chatbots across social media and messaging platforms that qualify leads and respond instantly — keeping client pipelines active around the clock without human intervention.
- ▸Delivered a Lead Management Dashboard giving clients real-time visibility into pipeline status and full bot conversation history — everything in one place.
- ▸Built a WhatsApp Task Delegation system where teams assign, track, and close tasks via text or voice note — eliminating app-switching and keeping everyone accountable.
Data Science Specialist
LogiScope Technologies Pvt. Ltd.
Focused on making sense of massive, noisy log data — building ML and deep learning backends that turned raw system logs into actionable intelligence for monitoring and reliability teams.
- ▸Ran deep EDA on large-scale log datasets to surface hidden patterns that manual monitoring consistently missed.
- ▸Built and deployed anomaly detection models using ML and DL algorithms that flagged system irregularities in real time — strengthening monitoring before issues escalated.
- ▸Experimented across multiple analytical techniques to identify the most reliable signals within complex log behaviour, turning raw data into clear, actionable outcomes.
- ▸Collaborated with cross-functional teams to integrate findings into data processing pipelines and improve anomaly reporting frameworks end-to-end.
Data Science Intern
Celebal Technologies
Worked within a professional data science team during a summer internship — getting hands-on with the full pipeline from raw data to deployed models, and applying Azure Cloud to bring it all together in a real production context.
- ▸Cleaned and preprocessed large datasets end-to-end, ensuring model inputs were reliable before a single line of training code ran.
- ▸Implemented ML algorithms against real business problems — moving from experimentation to predictive models with measurable outcomes.
- ▸Leveraged Azure Cloud services to understand how production-grade data applications are architected and deployed at scale.
- ▸Collaborated closely with senior data scientists, absorbing best practices and contributing to cross-functional project delivery.
03 / Leadership
College Leadership
Roles where I led people, ran initiatives, and created impact beyond the classroom.
AI/ML Lead
GDSC Poornima
Sep 2023 – Aug 2024
Owned the AI/ML vertical at GDSC Poornima for a full year — setting the technical direction, building the team's capabilities, and making machine learning genuinely accessible to the wider student body.
- ▸Turned abstract AI/ML research into hands-on projects that students could build, ship, and learn from.
- ▸Ran workshops that went beyond slides — giving peers practical exposure to tools and workflows used in industry.
- ▸Became the go-to mentor for students navigating ML projects and coursework, accelerating their learning curve.
- ▸Kept the AI/ML stream tightly integrated with GDSC's broader mission, ensuring every initiative moved the needle.
Student Ambassador — IDEA Lab
AICTE
Sep 2022 – Jul 2023
Represented AICTE's IDEA Lab on campus — connecting students with cutting-edge hardware like IoT, 3D printers, 3D scanners, and laser cutters, and turning raw curiosity into finished projects.
- ▸Ran workshops and hackathons that got school and college students building with real tools, not just reading about them.
- ▸Mentored students from first idea to working prototype — bridging the gap between imagination and execution.
- ▸Partnered with faculty to keep lab activities academically grounded while still pushing the boundaries of what students attempted.
Campus Ambassador
HackerEarth
Mar 2023 – Mar 2024
Was the face of HackerEarth on campus for a year — turning a platform into a movement by getting students to compete, collaborate, and grow as developers.
- ▸Built a thriving coding culture on campus through competitions and hackathons that pushed students beyond their comfort zone.
- ▸Forged partnerships with college clubs to extend HackerEarth's reach far beyond a single department.
- ▸Acted as the feedback loop between students and the platform — surfacing real insights that shaped better events.
Captain — Gaming & Development Club
Students' Council PIET
Oct 2022 – Sep 2023
Captained the Gaming and Development Club for a full academic year — shaping it into an active space where students built real skills in game development, not just played games.
- ▸Brought industry partnerships to life — collaborated with GoodGameNation to deliver events that went beyond what the college could offer alone.
- ▸Ran Blender and Unity workshops that gave students direct, tool-level exposure to the game development pipeline.
- ▸Created a club culture where members felt invested — turning casual interest into serious skill-building and collaboration.
Event Lead — Poornima Hackathon 2023
Poornima Institute of Engineering & Technology
Nov 2022 – Mar 2023
Drove the full lifecycle of Poornima Hackathon 2023 — from blank slate to a fully executed event — owning strategy, logistics, sponsors, and participant experience simultaneously.
- ▸Coordinated volunteers, sponsors, and stakeholders across every dimension of the event without letting anything slip.
- ▸Ran pre-hackathon workshops that raised the skill floor, so participants arrived ready to build rather than just learn.
- ▸Managed the budget and resource allocation end-to-end, keeping the event financially sound and operationally tight.
Event Lead — Rebel Yell 2.0
Hack Club Poornima
Dec 2023 – Jan 2024
Took full ownership of Rebel Yell 2.0 — from zero to a live college tech event — steering the team, the programme, the promotions, and the budget all at once.
- ▸Orchestrated a multi-track programme of speaker sessions, workshops, and activities that kept energy high throughout.
- ▸Led a team of volunteers with clear ownership and tight coordination, ensuring nothing fell through the cracks.
- ▸Built buzz through targeted promotions that drew a diverse, enthusiastic crowd well beyond the usual tech circle.
04 / Projects
Selected Work
AI/ML projects I've built — from LLM applications to production-grade ML systems.
Nexus AI
A multi-modal AI platform combining RAG, live web search, and six LLMs (Llama, Mixtral, Gemma, DeepSeek) in one interface — with real-time streaming, document upload, voice input, and LangGraph-powered node orchestration. Entire stack runs at zero cost.
Self-Driven Car
A neuroevolution simulator where AI learns to drive using NEAT — evolving neural networks across generations through mutation, crossover, and speciation. A 9-input network (8 ray-cast sensors + velocity) learns steering and acceleration with zero explicit rules.
05 / Research
Research
Papers I've published — at the intersection of AI, financial markets, and healthcare.
A Review of Deep Reinforcement Learning Techniques in Algorithmic and Quantitative Trading
A systematic review of DRL methods applied to algorithmic trading — benchmarking frameworks like AlphaOptimizerNet, QTNet, and FinRL against challenges of market volatility, transaction costs, and the exploration-exploitation tradeoff. Evaluates DDQN and RDMM approaches and outlines what is still needed before DRL systems are production-robust.
AI-Driven Medical Diagnostic System: Incorporating Deep Learning for a More Effective Healthcare Model
Presents a multi-modal diagnostic system combining deep learning and NLP to automate disease detection, medical image analysis, and drug identification. Integrates Gemini for real-time AI insights on a Django/React Native stack — targeting reduced diagnostic time, human error, and cost, especially in remote and underserved healthcare settings.
06 / Skills
Technical Skills
From raw data to deployed models — my toolkit across the full ML engineering stack.
07 / Certifications
Certifications
Credentials that validate my expertise across AI, ML, and data — from foundations to production.
WorldQuant Challenge — Silver Certificate
WorldQuantAwarded for strong performance in WorldQuant's quantitative research challenge — applying data-driven and algorithmic thinking to real financial markets.
Financial Analyst Career Track
365 Financial AnalystFinancial modelling, valuation, and data-driven investment analysis — adding a quantitative finance lens to complement my ML engineering background.
MLOps Specialization
DeepLearning.AI · CourseraBridges the gap between model training and production — CI/CD for ML, data pipelines, model monitoring, and scalable deployment practices.
TensorFlow: Advanced Techniques Specialization
DeepLearning.AI · CourseraGoes beyond standard TensorFlow — custom model architectures, advanced CV pipelines, and performance optimisation for production deployment.
TensorFlow Developer Specialization
DeepLearning.AI · CourseraEnd-to-end deep learning with TensorFlow — building and training neural networks for computer vision, NLP, and time series tasks.
Advanced Analytics Professional Certificate
Google · CourseraAdvanced-level data analytics with Python and statistical modelling — translating complex analysis into decisions that drive measurable outcomes.
Google Data Analytics Professional Certificate
Google · CourseraGoogle's professional data analytics track — data cleaning, SQL, R, and Tableau to turn raw data into clear, actionable insights.
Business Analytics & Digital Media
Indian School of Business · CourseraCovers data-driven decision making, digital marketing analytics, and business strategy — bridging the gap between ML outputs and real business impact.
Machine Learning Specialization
DeepLearning.AI · CourseraAndrew Ng's gold-standard ML curriculum — supervised, unsupervised, and reinforcement learning with a strong focus on real-world application.
Azure AI Fundamentals
MicrosoftValidates core AI and ML concepts on Microsoft Azure — the foundation for deploying AI services in cloud-native production environments.
Azure Data Fundamentals
MicrosoftValidates core data concepts on Azure — relational and non-relational databases, analytics workloads, and cloud data storage fundamentals.
08 / Contact
Get In Touch
Have a project in mind, want to collaborate on AI research, or just want to say hi?
Let's build something intelligent
I'm open to full-time AI/ML engineering roles, freelance projects, and research collaborations. If you have an interesting problem involving data or intelligence, I'd love to hear about it.
Location
Bengaluru, Karnataka, India
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