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DE - Cloud AI Engineer - F02
Ernst & Young
posted 17hr ago
Job Role Insights
Flexible timing
Key skills for the job
Job Description
- AI/ML Model Development
- Develop and train machine learning models using frameworks such as Autogen, PydanticAI, Langchain, TensorFlow, PyTorch, Scikit-learn.
- Leverage large language models (LLMs) and work on cloud LLM deployments.
- Build AI agents and have a solid understanding of agentic frameworks.
- Implement and fine-tune AI models for various business applications.
- AI/ML Deployment and Optimization
- Deploy machine learning models on cloud platforms (e.g., AWS, Azure, GCP).
- Optimize AI pipelines for both real-time and batch processing.
- Understand concepts around model fine-tuning, distillation, and optimization.
- Monitor and maintain the performance of deployed models, ensuring they meet business requirements.
- Cloud Integration
- Integrate AI/ML models with existing cloud infrastructure.
- Utilize cloud services (e.g., AWS SageMaker, Azure AI, GCP AI Hub) to manage AI workloads.
- Ensure compliance with data privacy and security standards.
- Collaboration and Support
- Work closely with the AI Architect to design scalable AI solutions.
- Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders.
- Provide technical support and troubleshooting for AI-related issues.
- Continuous Learning and Innovation
- Stay updated on the latest advancements in AI/ML technologies.
- Experiment with new AI tools and frameworks to enhance existing solutions.
- Contribute to the adoption of best practices for AI model lifecycle management.
Skills and attributes for success
- Proficiency in AI/ML frameworks such as Autogen, PydanticAI, Langchain, TensorFlow, PyTorch, Scikit-learn.
- Experience with cloud platforms AWS, Azure, GCP.
- Understanding of data engineering, ETL pipelines, and big data tools (e.g., Apache Spark, Hadoop).
- Hands-on experience with containerization and orchestration tools (Docker, Kubernetes).
- Knowledge of DevOps practices for AI/ML (MLOps).
- Strong understanding of deep learning models, including DNN, LSTM, Transformers, RL, and GNN.
- Experience with Generative AI technologies, including LLMs, model fine-tuning, distillation, and optimization.
- Strong problem-solving and analytical skills.
- Excellent communication and teamwork abilities.
- Ability to work in a fast-paced, collaborative environment.
Preferred Qualifications
- Certifications in cloud platforms (e.g., AWS Certified Solutions Architect, Azure AI Engineer) are a plus.
- Experience At least 5+ years in AI-related roles
- Proven experience in developing and deploying AI solutions with Python, JavaScript
- Strong background in machine learning, deep learning, and data modelling.
- Experience in integrating AI models with cloud infrastructure.
- Agile Methodologies Familiarity with Agile development practices and methodologies.
Education
- Bachelor s or master s degree in computer science, Engineering, or a related field.
Employment Type: Full Time, Permanent
Read full job descriptionPrepare for AI Engineer roles with real interview advice
What people at Ernst & Young are saying
AI Engineer salary at Ernst & Young
reported by
4
employees
with 3-4
years exp.
₹11.4
L/yr - ₹22
L/yr
39%
more
than the average AI Engineer Salary in India
View more details
What Ernst & Young employees are saying about work life
based on 10.6k employees
Flexible timing
Monday to Friday
No travel
Day Shift
Ernst & Young Benefits
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