AI/ML Engineer

• Design, develop, and train machine learning and deep learning models to solve business problems
• Build end-to-end ML pipelines data preprocessing, feature engineering, model training, evaluation, and deployment
• Develop and optimize deep learning architectures (CNNs, RNNs, Transformers) using PyTorch
• Deploy models into production environments and build scalable inference services
• Manage code repositories, branching strategies, and version control workflows using GitHub
• Collaborate with data engineers, product managers, and software engineers to integrate ML models into applications
• Conduct experiments, A/B tests, and performance benchmarking to improve model accuracy and efficiency
• Monitor deployed models for drift, performance degradation, and retraining needs
• Participate in code reviews and maintain CI/CD workflows via GitHub Actions
• Stay current with the latest AI/ML research and evaluate new techniques for applicability
• Document model architecture, experiments, and results clearly for technical and non-technical stakeholders

We are seeking an experienced AI/ML Engineer with 5+ years of hands-on experience building, training, and deploying machine learning models. The ideal candidate has mandatory expertise in Python, PyTorch, and GitHub and a strong track record of taking ML solutions from research to production., * 5+ years of professional experience in AI/ML engineering or data science

• Mandatory: Strong proficiency in Python writing clean, efficient, production-grade code
• Mandatory: Hands-on experience with PyTorch model building, training, and optimization
• Mandatory: Proficiency with GitHub version control, branching strategies, pull requests, code reviews, and collaborative workflows
• Solid understanding of machine learning fundamentals (supervised/unsupervised learning, model evaluation, regularization)
• Experience with deep learning concepts (neural networks, backpropagation, transfer learning)
• Experience with data manipulation libraries (NumPy, Pandas) and visualization tools (Matplotlib, Seaborn)
• Familiarity with model deployment tools/frameworks (Flask, FastAPI, TorchServe, Docker)
• Experience working with large datasets and data preprocessing pipelines
• Strong understanding of statistics, linear algebra, and probability
• Excellent problem-solving and analytical skills, * Experience with NLP (Transformers, BERT, LLMs) or Computer Vision
• Cloud platform experience (AWS SageMaker, Azure ML, Google Cloud Platform Vertex AI)
• Experience with MLOps tools (MLflow, Kubeflow, Airflow)
• Familiarity with distributed training (multi-GPU, Horovod, DDP)
• Experience with GitHub Actions for CI/CD automation
• Experience with vector databases and retrieval-augmented generation (RAG)
• Publications or contributions to open-source ML projects