Hello! I'm

Vinayak Mane

AI Engineer & Machine Learning Specialist

About

About Me

Vinayak Mane

Vinayak Mane

AI Engineer & ML Specialist

Personal Info

Name: Vinayak Mane
Job Role: AI Engineer
Location: Melbourne, Australia

Key Skills

Python & Deep Learning 95%
Large Language Models 90%
Neural Networks 88%
Natural Language Processing 85%
Computer Vision 82%
MLOps & Cloud 80%

Passionate AI Engineer with 3+ years of professional experience in building intelligent systems that solve real-world problems. Specializing in Large Language Models (LLMs), Neural Networks, and Machine Learning pipelines, I create cutting-edge AI solutions that drive innovation. With a Master's in AI from Monash University, I combine academic rigor with practical industry experience to develop scalable AI applications.

Experience: 3+ Years in AI/ML Engineering (2021-Present)
Specialization: Large Language Models & Neural Networks
Education: Master's in AI, Monash University (Feb 2024 - Dec 2025)
Languages: English, Marathi, Hindi
Core Expertise: LLMs, Deep Learning, NLP, Computer Vision, MLOps
Tech Stack: Python, TensorFlow, PyTorch, LangChain, AWS, Docker, FastAPI
Research Focus: Generative AI, RAG Systems, Neural Architecture Search
Interests: AI Research, Open Source, Tech Innovation

Experience

Professional Journey

3+ Years of AI/ML Experience · Machine Learning · Deep Learning · MLOps

T
NOV 2024 - PRESENT (1 year 2 months)

Consultant

TELSTRA · Part-time

Melbourne, Victoria, Australia · On-site

  • Leveraged Salesforce CRM (Console) to manage customer data, streamline workflows, and support data-driven decisions
  • Coordinated with teams to ensure smooth operations and resolved conflicts effectively through strong communication
  • Built skills in CRM systems, stakeholder engagement, and problem-solving, with exposure to AI-driven customer experience opportunities
JUNE 2023 - JAN 2024 (8 months)

Machine Learning Engineer

BLUJAY ROBOTICS PRIVATE LIMITED · Full-time

Pune, Maharashtra, India

  • Built ML solutions for robotic systems, implementing YOLO, CNNs, and ANNs for real-time object detection
  • Developed a Python-based control system, improving automation, accuracy, and efficiency in robotics workflows
  • Collaborated with engineers to integrate AI models into production, balancing research with deployment
DF
NOV 2022 - JUNE 2023 (8 months)

Data Science Engineer

DELTAFOUR · Full-time

Bangalore · Remote

  • Led a predictive maintenance (PdM) project, using LSTM and ensemble models for anomaly detection and fault classification
  • Designed and deployed an MLOps pipeline with CI/CD, Docker, and AWS EC2, enabling scalable model training and deployment
  • Coordinated with cross-functional teams to deliver insights from real-time industrial pump data, driving data-informed decisions
C
OCT 2021 - NOV 2022 (1 year 2 months)

Research & Development Engineer

CIE AUTOMOTIVE

Aurangabad, Maharashtra, India · On-site

  • Applied ML to optimize HPDC processes, improving cycle stability and quality
  • Built defect-prediction models (porosity, cold shuts, misruns) from machine logs and sensor data
  • Developed anomaly detection & tool-wear prediction systems to reduce scrap and unplanned downtime
  • Collaborated with production teams to convert model insights into better parameter windows and higher first-pass yield


Education


FEB 2024 - DEC 2025

Master's of Artificial Intelligence

Monash University, Australia

Completed advanced coursework in Machine Learning, Deep Learning, Neural Networks, Natural Language Processing, Computer Vision, and AI Ethics. Specialized in Large Language Models and production-ready AI systems.

2018 - 2021

Bachelor of Technology

College of Engineering Pune (COEP)

Graduated with strong foundations in engineering principles, programming, data structures, algorithms, and mathematics.

Download CV

AI Projects

Innovative AI Solutions

Cutting-edge projects showcasing the power of artificial intelligence

Top 3 Featured Projects

Highlighting my most impactful and comprehensive AI/ML projects

AI-Powered Predictive Maintenance

NASA Turbofan Engine Remaining Useful Life Prediction

Tech Stack:

Python | TensorFlow | MLOps | Docker | AWS | CI/CD

  • - Built intelligent system to predict remaining useful life of jet engines
  • - Implemented advanced regression algorithms and ensemble methods
  • - Full MLOps pipeline with CI/CD, containerization, and cloud deployment
View Code

Deep Learning Computer Vision

Multi-Class Dog Breed Image Classification System

Tech Stack:

TensorFlow | Keras | OpenCV | ResNet | InceptionNet | MobileNet

  • - Developed sophisticated image classification system for dog breed identification
  • - Implemented state-of-the-art CNN architectures (ResNet, InceptionNet, DenseNet)
  • - Achieved high accuracy through transfer learning and data augmentation
View Code

NLP & Transformer Models

Quora Duplicate Question Detection with BERT & RoBERTa

Tech Stack:

BERT | RoBERTa | Transformers | GloVe | Scikit-learn

  • - Solved Quora's duplicate question detection challenge
  • - Implemented BERT and RoBERTa transformer encoders
  • - Combined with traditional ML approaches using GloVe embeddings and ensembles
View Code

Other Projects

Additional AI/ML projects demonstrating diverse technical skills


Time Series Forecasting AI

Retail Sales Prediction with LSTM & Statistical Models

Tech Stack:

Python | LSTM | ARIMA | Prophet | TensorFlow | Pandas

  • - Developed advanced time series forecasting models for retail sales
  • - Implemented LSTM neural networks, ARIMA, and Facebook Prophet
  • - Achieved accurate demand forecasting with multiple ML algorithms
View Code

Unsupervised Learning & Clustering

Customer Segmentation with K-Means & DBSCAN

Tech Stack:

Python | K-Means | DBSCAN | PCA | Scikit-learn | Pandas

  • - Built intelligent customer segmentation system
  • - Applied K-Means clustering, DBSCAN, and PCA dimensionality reduction
  • - Identified customer patterns and provided personalized recommendations
View Code

IMDB Sentiment Analysis MLOps

End-to-End ML Pipeline with Kubernetes & Monitoring

Tech Stack:

Python | Flask | Docker | Kubernetes | DVC | MLflow | AWS EKS | Prometheus | Grafana

  • - Built end-to-end MLOps pipeline for sentiment analysis
  • - Implemented CI/CD with GitHub Actions and containerized deployment on AWS EKS
  • - Model versioning with MLflow and monitoring with Prometheus & Grafana
View Code

Contact

Contact Me

Below are the details to reach out to me!

Address

Melbourne , Australia

Contact Number

+61 0468470514

Email Address

manevinayakv.47@gmail.com

Download Resume

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