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Role & responsibilities We are seeking an experienced and technically strong Machine Learning Engineer to design, implement, and operationalize ML models across Google Cloud Platform (GCP) and Microsoft Azure. The ideal candidate will have a robust foundation in machine learning algorithms, MLOps practices, and experience deploying models into scalable cloud environments. Responsibilities: Design, develop, and deploy machine learning solutions for use cases in prediction, classification, recommendation, NLP, and time series forecasting. Translate data science prototypes into production-grade, scalable models and pipelines. Implement and manage end-to-end ML pipelines using: Azure ML (Designer, SDK, Pipelines), Data Factory, and Azure Databricks Vertex AI (Pipelines, Workbench), BigQuery ML, and Dataflow Build and maintain robust MLOps workflows for versioning, retraining, monitoring, and CI/CD using tools like MLflow, Azure DevOps, and GCP Cloud Build. Optimize model performance and inference using techniques like hyperparameter tuning, feature selection, model ensembling, and model distillation. Use and maintain model registries, feature stores, and ensure reproducibility and governance. Collaborate with cloud architects, and software engineers to deliver ML-based solutions. Maintain and monitor model performance in production using Azure Monitor, Prometheus, Vertex AI Model Monitoring, etc. Document ML workflows, APIs, and system design for reusability and scalability. Primary Skills required (Must Have Expereince): 5 -7 years of experience in machine learning engineering or applied ML roles. Advanced proficiency in Python, with strong knowledge of libraries such as Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, TensorFlow, PyTorch. Solid understanding of core ML concepts: supervised/unsupervised learning, cross-validation, bias-variance tradeoff, evaluation metrics (ROC-AUC, F1, MSE, etc.). Hands-on experience deploying ML models using: Azure ML (Endpoints, SDK), AKS, ACI Vertex AI (Endpoints, Workbench), Cloud Run, GKE Familiarity with cloud-native tools for storage, compute, and orchestration: Azure Blob Storage, ADLS Gen2, Azure Functions GCP Storage, BigQuery, Cloud Functions Experience with containerization and orchestration (Docker, Kubernetes, Helm). Strong understanding of CI/CD for ML, model testing, reproducibility, and rollback strategies. Experience implementing drift detection, model explainability (SHAP, LIME), and responsible AI practices.

Designation: AI/ML Engineer Experience : 2 - 5 years exp Education : Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related fields Job Location: Navi Mumbai (Onsite) Role. Key Responsibilities: Design and develop AI/ML models for OCR, focusing on handwritten, printed, and multi-language documents. Train and fine-tune custom OCR models using frameworks like TensorFlow, PyTorch, or Google Vertex AI, etc. Integrate OCR solutions into a browser-based platform using Node.js (backend) and React.js (frontend). Preprocess and analyze scanned or photographed documents to improve text recognition accuracy using tools like OpenCV. Evaluate and compare third-party OCR services (e.g., Google Vision, Azure OCR, Amazon Textract). Build intelligent data pipelines for document parsing, classification, and information extraction. Collaborate with full-stack developers to deploy AI models into production web apps. Keep up to date with advancements in AI tools, OCR technologies, and web integration strategies. Experience in diagram or symbol detection Required Skills & Qualifications:* Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related fields 3+ years of proven experience with OCR technologies and document image processing Strong proficiency in Python for model development, training, and data pipelines Working knowledge of JavaScript, Node.js, and React.js for full-stack AI integration Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, or similar) Demonstrated ability to preprocess and enhance document images using OpenCV or similar tools. Experience deploying ML models to production environments. Familiarity with version control (Git), containerization (Docker), and cloud services (AWS/GCP/Azure) *Good to Have Skills:* Experience with Agentic AI frameworks (LangChain, AutoGPT, or similar) Knowledge of RAG (Retrieval-Augmented Generation) architectures for document context Familiarity with LLM integration for enhanced document understanding Experience with multi-language document processing and non-Latin character recognition Understanding of diagram, table, and technical symbol detection in documents Background in MLOps tools (MLflow, DVC, Vertex AI) for model lifecycle management Experience developing autonomous AI agents for document processing automation Familiarity with prompt engineering for specialized OCR applications Interested candidate can apply there resume on email id :- hr@techplusinfotech.com .