Parth Kalkar

I’m a full-stack AI engineer with 5+ years of experience building production-grade machine learning systems end-to-end. My work spans LLM engineering, agentic workflows, multimodal ML, computer vision, embeddings, retrieval, and efficient on-device inference. I thrive when taking ideas from data → model → API → deployment and turning them into real, usable AI products. At BMW, I design and deploy AI-driven systems that accelerate design workflows, automate repetitive processes, and enable teams to explore concepts faster using computer vision, representation learning, and intelligent retrieval. My role sits at the intersection of engineering and product — understanding creative workflows, identifying bottlenecks, and building practical AI tools that meaningfully improve speed and quality. In parallel, I’ve built several independent, ML-first products from scratch, including: 1. Agentic AI assistants with multi-step reasoning and tool-use 2. RAG-based research systems for fast knowledge extraction 3. OCR + detection pipelines using YOLO and transformer-based models 4. Mobile learning apps powered by multimodal AI and step-by-step reasoning 5. Food-distribution platforms using predictive modeling and workflow automation In each project, I own the full lifecycle: data engineering, model development and fine-tuning, evaluation, optimization (quantization/distillation), API design, backend infrastructure, deployment, and iterative improvements based on real user feedback. 🧰 Core Capabilities 1. ML & LLM Engineering: Transformers, agentic systems, RAG, PEFT, embeddings, CV 2. Full-Stack AI: FastAPI, Python, vector databases, backend systems, orchestrated workflows 3. MLOps & Infra: Docker, MLflow, scalable serving, monitoring, cloud deployment 4. Efficient / On-Device AI: quantization, pruning, distillation, CPU/GPU-optimized inference 5. Product & Strategy: rapid prototyping, UX-focused design, AI product lifecycle ownership 6. Cross-Functional Leadership: translating ambiguous ideas into clear technical roadmaps I care deeply about building AI systems that work in the real world — fast, reliable, explainable, and aligned with how people actually solve problems. Whether it’s designing an agentic workflow, optimizing a model for edge devices, or turning a vague idea into a deployed AI product, I love the entire process. If you’re building something ambitious in applied AI, I’d love to connect.