AI Engineers

Responsibilities :

Key Responsibilities Design, develop, and deploy machine learning and AI models Build and maintain data pipelines for training and inference Work on supervised and unsupervised learning algorithms Implement NLP, Computer Vision, or Deep Learning solutions Optimize models for performance, scalability, and accuracy Collaborate with data engineers, analysts, and product teams Deploy models using cloud platforms (AWS/Azure/GCP) Monitor model performance and perform continuous improvements Conduct data preprocessing, feature engineering, and model evaluation Document models, processes, and experiments Required Skills & Qualifications Technical Skills Strong proficiency in Python Experience with Machine Learning libraries: Scikit-learn TensorFlow / PyTorch Knowledge of data manipulation tools (Pandas, NumPy) Experience with ML algorithms (regression, classification, clustering) Familiarity with Deep Learning frameworks Knowledge of NLP or Computer Vision techniques Experience in model deployment (APIs, microservices) Strong understanding of statistics and probability

Additional Responsibilities:

Preferred Skills (Nice-to-Have) Experience with Generative AI / LLMs (GPT, LangChain, Hugging Face) Knowledge of MLOps tools (MLflow, Kubeflow, Airflow) Experience with Docker and Kubernetes Familiarity with Big Data tools (Spark, PySpark) Experience with REST APIs and microservices architecture Knowledge of cloud AI services (AWS SageMaker, Azure ML, GCP AI) Understanding of vector databases and embeddings (FAISS, Pinecone) Exposure to CI/CD pipelines and DevOps practices

Technical and Professional Requirements:

Primary skills:Domain- Turbomachinery- Steam Turbine- Rotor