Ai engineer- Genrative Ai

This role is for one of the Weekday's clients

Salary range : Rs 2000000 - Rs 3500000 (ie INR 20-35 LPA)

Min Experience : 5 years

Location : Hyderabad, Chennai

JobType : full-time

As an AI / ML Engineer, you will be responsible for creating end-to-end machine learning solutions—from data exploration to model deployment. You will work closely with cross-functional teams to understand requirements, develop ML pipelines, test model performance, and integrate solutions into production environments.

Your responsibilities will involve leveraging Python, ML libraries, TensorFlow, PyTorch, and cloud tools to build efficient, scalable AI systems. Experience with Google Cloud Platform, particularly Vertex AI, will enable you to accelerate model development, orchestration, and deployment. You will also collaborate with peers, contribute to architectural decisions, and troubleshoot model or pipeline issues to ensure reliable outcomes.

Requirements

Key Responsibilities

• Model Development :  Build, train, and optimize AI / ML models using frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• End-to-End ML Pipeline :  Design and implement complete machine learning workflows including data preparation, feature engineering, training, testing, and deployment.
• Cloud-Based AI Work :  Work with Google Cloud Platform services and tools for scalable model training, storage, monitoring, and deployment.
• Vertex AI Implementation :  Utilize Vertex AI (if experienced) for automated ML, model registry, feature store, pipelines, and real-time deployment.
• Model Evaluation :  Perform model testing, validation, and tuning to ensure accuracy, reliability, and performance.
• Collaboration :  Work with data engineers, product teams, and developers to integrate ML models into products or applications.
• Problem Solving :  Analyze technical challenges, debug issues, and propose innovative solutions based on best practices.
• Documentation :  Maintain detailed documentation for model logic, workflows, and deployment guidelines.
• Continuous Improvement :  Research emerging AI technologies, frameworks, and cloud capabilities to improve existing systems.
• Scalability & Optimization :  Ensure models and pipelines are efficient, secure, maintainable, and scalable for long-term use.

What Makes You a Great Fit