Hello! I’m Anish Nilesh Rane, a Generative AI and Machine Learning Engineer passionate about transforming real-world
challenges into intelligent, scalable solutions.
My journey began in mechanical engineering, designing hydraulic systems and CAD models, but curiosity pulled me
deeper into data, automation, and AI-driven products. Today, I bridge these worlds, engineering precision with AI
innovation, to build solutions that are not only technically sound but also business-impactful.
My Story
I’m currently working as an Application Engineer – Artificial Intelligence & Machine Learning at Weichai Power, a global leader in diesel engines, new energy solutions, and intelligent manufacturing.
At Weichai, my role revolves around designing AI-driven tools that accelerate engineering workflows, improve
decision-making, and drive operational efficiency. Whether it’s predictive maintenance models that reduce downtime,
CAD-Llama–powered digital twins, or cloud-integrated dashboards connecting sales and engineering, I thrive at the
intersection of AI, automation, Research and Development and manufacturing.
Weichai’s mission is to push the boundaries of mobility and power systems, and I am proud to contribute by making their
processes smarter, faster, and more adaptive.
What I Build
- AI-Driven Dashboards: Python + SQL systems powered by open-source LLMs like Llama 3.1, cutting response times by 35%.
- RAG Search Engines: Technical knowledge bases (Qwen2:0.5B) that boost query accuracy by 60%.
- Predictive Maintenance Models: LSTM networks that proactively minimize failures and save resources.
- Digital Twin Integrations: CAD models in CATIA/SolidWorks merged with AI for manufacturability and anomaly detection.
- Automation Pipelines: Cloud-hosted (AWS) tools streamlining invoices, templates, and inventory forecasting.
In short: I design end-to-end AI ecosystems from research to production with measurable impact.
Projects I’m Proud Of
- Insurance Policy Chatbot (2025): Built a GPT-powered retrieval pipeline with embeddings and dual-stage retrieval for grounded Q&A.
- Travel Planner Bot (2024): Integrated GPT with Amadeus + weather APIs to deliver personalized, real-time itineraries.
- Gesture Recognition (2023): 3D-CNN + ConvLSTM achieving 78% validation accuracy for human-computer interaction.
- Semantic Fake News Detection (2023): Word2Vec + logistic regression pipeline with 91% accuracy and strong F1 performance.
- Bike Demand Prediction (2023): MLR model (R² = 0.82) for rental inventory optimization.
Each project reflects my love for tackling problems where data meets human experience.
Skills That Define Me
- Machine Learning & AI: PyTorch, TensorFlow, Scikit-learn, LLM fine-tuning, RAG pipelines.
- Data & Analytics: Pandas, NumPy, SQL/NoSQL, Power BI, advanced visualization.
- Cloud & MLOps: AWS, Docker, Kubernetes, CI/CD for AI solutions.
- Programming: Python (my go-to), R, C++, JavaScript.
- Engineering Roots: CAD modeling, hydraulic systems, DFA/DFM principles.
What makes me different is not just technical depth, but the ability to translate complexity into clarity, aligning
AI solutions with business impact.
Education & Growth
- PG Diploma in Machine Learning & AI – IIIT, First-Class with Distinction
- B.E. Mechanical Engineering – SPPU, First-Class with Distinction
- Diploma in Mechanical Engineering – MSBTE, First-Class with Distinction
I believe learning is never done. My growth has always come from pushing boundaries, experimenting with new tools, and
blending my engineering foundation with modern AI capabilities.
Beyond Work
When I’m not debugging code or optimizing neural nets, you’ll probably find me:
- Sketching ideas for new AI tools.
- Breaking down complex concepts into teaching content.
- Exploring how AI can merge with mobility, manufacturing, and smart energy — fields where companies like Weichai are already leading the charge.
✨ Thanks for visiting my corner of the web. My goal is simple: to engineer intelligence that powers progress. If that excites you too, let’s connect.