AI machine learning engineer

**AI / Machine Learning Engineer** **Role Summary** **We are looking for a pure AI / ML Engineer with 3 to 4 years of experience who can design, train, evaluate, and deploy machine learning models into production systems.** This role covers computer vision, classical machine learning, and deep learning use cases. This is not a data analyst role and not a prompt\-engineering role. You are expected to work with datasets, models, training pipelines, and production inference end to end. **Key Responsibilities Model Development \& Training** ● Design and train machine learning and deep learning models for real\-world use cases ● Work across problem types: ○ Computer vision ○ Tabular data (classification, regression) ○ Time\-series forecasting ○ Anomaly detection ● Select appropriate algorithms instead of defaulting to deep learning ● Perform hyperparameter tuning and model optimization ● Analyze model failures and iterate based on data, not guesswork Data \& Feature Engineering ● Understand, clean, and preprocess structured and unstructured datasets ● Perform feature engineering for classical ML models ● Handle: ○ Missing data ○ Outliers ○ Class imbalance ○ Label noise ● Design proper train/validation/test strategies ● Prevent data leakage and evaluation mistakes Computer Vision ● Build and deploy CV models for tasks such as: ○ Image classification ○ Object detection ○ Segmentation ● Work with image preprocessing, augmentation, and labeling workflows ● Fine\-tune pre\-trained vision models when appropriate Deployment \& Production ● Convert trained models into production\-grade inference services ● Deploy models via APIs, batch pipelines, or streaming systems ● Optimize inference for: ○ Latency ○ Throughput ○ Cost ● Integrate models with backend systems and products ● Monitor model performance and retrain when needed MLOps \& Lifecycle Management ● Build and maintain end\-to\-end ML pipelines ● Track experiments, datasets, and model versions ● Automate training, evaluation, and deployment ● Implement rollback and version control for models ● Monitor model drift and data distribution changes Required Skills \& Experience Core ML Knowledge ● Strong foundation in: ○ Machine learning algorithms ○ Statistics \& probability ○ Linear algebra ● Clear understanding of when to use: ○ Linear models ○ Tree\-based models ○ Neural networks Tools \& Frameworks ● Strong experience with Python ● Experience with ML frameworks: ○ scikit\-learn ○ PyTorch and/or TensorFlow ● Experience with computer vision tools (OpenCV, torchvision, etc.) ● Familiarity with model evaluation metrics across different problem types Deployment \& Engineering ● Experience deploying ML models into production ● Familiarity with: ○ Docker and containerized ML services ○ Model serving frameworks ○ Cloud or on\- prem deployment environments ● Ability to write maintainable, testable ML code (not just notebooks)