[For Hire] AI/ML Engineer | LLMs, RAG, FastAPI, AWS
Hi everyone,
I’m a recent Computer Science graduate from India actively looking for AI/ML Engineer / Applied AI / ML Developer opportunities (remote or on-site).
I have 6+ months of startup experience across 2 remote roles, where I’ve worked on production-grade AI systems, ML pipelines, and full-stack AI products. I currently have a PPO, but I’m exploring opportunities where I can work on challenging AI problems, learn from strong teams, and contribute meaningfully from day one.
What I’ve worked on
AI/ML Engineering
- Built and optimized real-world ML inference pipelines, reducing latency from 5s → 300ms (94% improvement) using batching and async processing on AWS + Databricks
- Worked on training, evaluating, and improving production models, including tuning precision/recall tradeoffs, threshold calibration, and iterative feature engineering
- Improved ensemble model agreement from 30% → 68%
- Built retraining workflows for handling model performance shifts as data changed over time
- Developed a model-drift monitoring pipeline used daily by hundreds of data scientists to track performance degradation and trigger investigation
- Designed LLM guardrails (rule-based + embedding-based), reducing unsafe outputs by 54%
- Worked extensively with RAG pipelines, LangChain, HuggingFace Transformers, DistilBERT, NER, NLP
- Built and deployed FastAPI inference APIs integrated into production microservices
Modeling Fundamentals
- Trained neural networks from scratch using only NumPy to deepen my understanding of backpropagation, optimization, and model internals
- Strong interest in understanding systems beyond libraries—not just using frameworks, but understanding how models actually work underneath
LLM & Evaluation Work
- Worked with medical-focused Small Language Models (SLMs) and benchmarked their outputs against frontier models like ChatGPT, Claude, and Gemini
- Experience evaluating model behavior, response quality, safety, and consistency across different architectures
Cloud / Infrastructure
- AWS (SageMaker, Lambda, S3)
- Databricks
- Docker
- GitHub Actions / CI/CD
- PostgreSQL / Redis
- Linux
Full Stack AI Development
- Built AI SaaS products using React, Next.js, Node.js, FastAPI, tRPC
- Developed scalable backend services and real-time APIs
- Integrated third-party APIs and workflow automation systems
Notable Projects
1. AI Threat Intelligence Platform (Cybersecurity + ML)
- Built an end-to-end threat intelligence platform combining ML + NLP + security automation
- Achieved 96% phishing email classification accuracy using fine-tuned DistilBERT
- Built hybrid IOC extraction pipeline (NER + regex) for malware indicator extraction
- Full-stack deployment with React + FastAPI
- Patent pending on the underlying AI-based threat intelligence and IOC classification system
2. Visual AI Workflow Builder
- Built a drag-and-drop AI workflow platform for designing and executing LLM pipelines
- 30+ integrations
- Real-time execution using LangChain
- Type-safe APIs and multi-user workflow persistence
3. Emotion-Aware Memory Engine (Research / Ongoing)
- Working on an AI architecture with a pending patent focused on an emotion-aware memory engine
- Exploring adaptive local memory, context retention, and persistent personalization for more human-like model behavior across sessions
Tech Stack
Python, JavaScript, C++, PyTorch, Scikit-learn, XGBoost, HuggingFace, LangChain, FastAPI, React, Next.js, Node.js, AWS, Databricks, PostgreSQL, Docker
Achievements
- Runner-up, National CTF (400+ teams) — reverse engineering, web exploitation, and forensics
- Top performer, AWS Cloud Security CTF
- Patent pending on AI-based intelligent systems
Open to:
✅ AI/ML Engineer roles
✅ Applied AI / LLM Engineer roles
✅ Machine Learning Engineer roles
✅ AI startups / research-driven teams
✅ ML + Security / Cyber AI roles
Location: India (Open to remote / international opportunities)
If you think I could be a fit for your team, feel free to DM me — happy to share my resume and chat.
Thanks!