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Generative AI Engineer
3 months ago
Job Description
As an Assistant Manager - Generative AI Engineer, you will be responsible for developing and implementing advanced AI models and algorithms to solve complex problems and deliver innovative solutions. You will work closely with the IT team and other stakeholders to understand the business requirements and translate them into technical solutions.
Responsibilities of Generative AI Engineer
Provided below are the responsibilities of a Generative AI Engineer :
- 1. Design, develop, and implement generative AI models and algorithms.
- 2. Work with large and complex data sets to evaluate, recommend, and support the implementation of business strategies.
- 3. Optimize AI/ML models for scalability and performance.
- 4. Collaborate with cross-functional teams to understand business requirements and provide AI-driven solutions.
- 5. Stay updated with the latest technological trends in AI and ML.
- 6. Use Big Data technologies like Hadoop, Spark, and others to handle the data effectively.
- 7. Use Python, TensorFlow, PyTorch, GPT, BERT, Scikit-Learn, and other technologies for developing AI models.
- 8. Manage data storage solutions using MongoDB, Databricks, Hive, Apache Kafka, Apache Spark, etc.
- 9. Ensure the accountability and reliability of the solutions provided.
- 10. Adapt to changing business needs and align the AI solutions accordingly.
- 11. Use analytical thinking to understand complex problems and devise effective solutions.
- 12. Pay attention to detail to ensure the accuracy and reliability of data and models.
- 13. Communicate effectively with team members and stakeholders.
- 14. Manage changes effectively to ensure minimal disruption to the business.
- 15. Use business acumen to understand the impact of AI solutions on the business.
- 16. Use critical thinking and decision-making skills to choose the best solutions.
- 17. Analyze data to make informed decisions.
- 18. Resolve conflicts effectively to ensure smooth project execution.
- 19. Special emphasis should be placed on the development and optimization of generative AI models.
Functional Competencies
- 1. Generative AI: The candidate should have a strong understanding of generative models such as GANs and VAEs, and should be able to design and implement these models for various applications.
- 2. Machine Learning and Optimization: The candidate should have a solid understanding of machine learning algorithms and optimization techniques.
- 3. Big Data Technologies: The candidate should have experience with big data technologies such as Hadoop, Spark, and Hive.
- 4. Python, TensorFlow, PyTorch: The candidate should be proficient in Python and have experience with machine learning libraries such as TensorFlow and PyTorch.
- 5. GPT, BERT, ScikitLearn: The candidate should have experience with NLP models like GPT and BERT, and machine learning libraries like ScikitLearn.
- 6. MongoDB, Databricks: The candidate should have experience with database systems like MongoDB and big data platforms like Databricks.
- 7. Apache Kafka, Apache Spark: The candidate should have experience with streamprocessing software platform Apache Kafka, and opensource distributed generalpurpose clustercomputing framework Apache Spark.
Behavioural Competencies
- 1. Accountability: The candidate should take responsibility for their actions and decisions.
- 2. Adaptability: The candidate should be able to adjust to new conditions.
- 3. Analytical Thinking: The candidate should be able to simplify complex problems and analyze them systematically.
- 4. Attention to Detail: The candidate should be able to concentrate on detailed aspects.
- 5. Communication: The candidate should be able to convey information effectively.
- 6. Change Management: The candidate should be able to manage, adapt to, and instigate change.
- 7. Business Acumen: The candidate should understand and deal with a business situation in a manner that is likely to lead to a good outcome.
- 8. Critical Thinking: The candidate should be able to objectively analyze and evaluate an issue in order to form a judgment.
- 9. Decision Making: The candidate should be able to make decisions quickly and effectively.
- 10. Data Analysis: The candidate should be able to inspect, clean, transform, and model data with the goal of discovering useful information.
- 11. Conflict Resolution: The candidate should be able to handle and resolve conflicts in a manner that is constructive for all parties involved.
Good to have skills
- 1. Focus: The candidate should have the ability to concentrate on a task over a period of time without being distracted. This is especially important in a role such as this, where attention to detail and the ability to stay focused on complex tasks is crucial.
Employee type : Fulltime
Work Location: Hyderabad