AI Engineers

Key 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

Technical Requirements:

• Primary skills Domain Turbomachinery Steam Turbine Rotor

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

Preferred Skills:

Technology->AI-AI Engineering->AI/ML Solution Architecture and Design