AI ML Engineer
Oracle
Date: 5 days ago
City: Ahmedabad, Gujarat
Contract type: Full time
Job Description
Job Description: As an AI Engineer, you will work closely with cross-functional teams to design, build, and deploy AI solutions in a scalable and efficient manner. You will be responsible for leveraging Docker and Kubernetes for containerization and orchestration, implementing MLOps practices and utilizing your skills in python and machine learning to build and enhance our AI models. Experience in Generative AI is highly desired as we continue to push the boundaries of AI applications.
Responsibilities:
Design and develop AI/ML models and systems from prototyping to production, while ensuring scalability and efficiency.
Utilize Docker and Kubernetes for containerization, deployment and orchestration of AI models and services in production environments.
Implement and manage end-to-end MLOps pipelines to automate model training, testing, deployment and monitoring.
Build robust, reusable, and scalable Python code for AI model development and deployment.
Work on the integration and deployment of generative AI models and systems for innovative applications.
Troubleshoot, optimize and maintain production-level AI models and services.
Stay up-to-date with the latest trends and advancements in AI, machine learning and MLOps technologies.
Requirements:
Bachelor's or Master’s degree in Computer Science, Engineering or related field.
Proven experience (3+ years) in AI/ML engineering with a strong focus on Docker, Kubernetes, and MLOps.
Expertise in Python and frameworks/libraries such as TensorFlow, PyTorch, Scikit-learn or similar.
Solid understanding of machine learning algorithms and techniques, particularly in deep learning and natural language processing (NLP).
Hands-on experience deploying and managing AI models in production using Docker and Kubernetes.
Knowledge of cloud platforms and how they relate to containerized AI deployments.
Experience with CI/CD pipelines and version control (Git).
Strong understanding of generative AI models such as GANs, VAEs or transformers.
Familiarity with monitoring, logging, and debugging AI/ML systems in production environments.
Excellent communication and teamwork skills, with the ability to collaborate with diverse teams.
Preferred Qualifications:
Experience with large-scale AI model deployments.
Knowledge of additional languages such as Java, Go or C++.
Familiarity with data engineering tools and frameworks (Apache Kafka, Spark etc.).
Exposure to AI ethics and governance.
Career Level - IC3
Responsibilities
Job Description: As an AI Engineer, you will work closely with cross-functional teams to design, build, and deploy AI solutions in a scalable and efficient manner. You will be responsible for leveraging Docker and Kubernetes for containerization and orchestration, implementing MLOps practices and utilizing your skills in python and machine learning to build and enhance our AI models. Experience in Generative AI is highly desired as we continue to push the boundaries of AI applications.
Responsibilities:
Design and develop AI/ML models and systems from prototyping to production, while ensuring scalability and efficiency.
Utilize Docker and Kubernetes for containerization, deployment and orchestration of AI models and services in production environments.
Implement and manage end-to-end MLOps pipelines to automate model training, testing, deployment and monitoring.
Build robust, reusable, and scalable Python code for AI model development and deployment.
Work on the integration and deployment of generative AI models and systems for innovative applications.
Troubleshoot, optimize and maintain production-level AI models and services.
Stay up-to-date with the latest trends and advancements in AI, machine learning and MLOps technologies.
Requirements:
Bachelor's or Master’s degree in Computer Science, Engineering or related field.
Proven experience (3+ years) in AI/ML engineering with a strong focus on Docker, Kubernetes, and MLOps.
Expertise in Python and frameworks/libraries such as TensorFlow, PyTorch, Scikit-learn or similar.
Solid understanding of machine learning algorithms and techniques, particularly in deep learning and natural language processing (NLP).
Hands-on experience deploying and managing AI models in production using Docker and Kubernetes.
Knowledge of cloud platforms and how they relate to containerized AI deployments.
Experience with CI/CD pipelines and version control (Git).
Strong understanding of generative AI models such as GANs, VAEs or transformers.
Familiarity with monitoring, logging, and debugging AI/ML systems in production environments.
Excellent communication and teamwork skills, with the ability to collaborate with diverse teams.
Preferred Qualifications:
Experience with large-scale AI model deployments.
Knowledge of additional languages such as Java, Go or C++.
Familiarity with data engineering tools and frameworks (Apache Kafka, Spark etc.).
Exposure to AI ethics and governance.
Diversity & Inclusion:
An Oracle career can span industries, roles, Countries and cultures, giving you the opportunity to flourish in new roles and innovate, while blending work life in. Oracle has thrived through 40+ years of change by innovating and operating with integrity while delivering for the top companies in almost every industry.
In order to nurture the talent that makes this happen, we are committed to an inclusive culture that celebrates and values diverse insights and perspectives, a workforce that inspires thought leadership and innovation. .
Oracle offers a highly competitive suite of Employee Benefits designed on the principles of parity, consistency, and affordability. The overall package includes certain core elements such as Medical, Life Insurance, access to Retirement Planning, and much more. We also encourage our employees to engage in the culture of giving back to the communities where we live and do business.
At Oracle, we believe that innovation starts with diversity and inclusion and to create the future we need talent from various backgrounds, perspectives, and abilities. We ensure that individuals with disabilities are provided reasonable accommodation to successfully participate in the job application, interview process, and in potential roles. to perform crucial job functions.
That’s why we’re committed to creating a workforce where all individuals can do their best work. It’s when everyone’s voice is heard and valued that we’re inspired to go beyond what’s been done before.
About Us
As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s problems. True innovation starts with diverse perspectives and various abilities and backgrounds.
When everyone’s voice is heard, we’re inspired to go beyond what’s been done before. It’s why we’re committed to expanding our inclusive workforce that promotes diverse insights and perspectives.
We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity.
Oracle careers open the door to global opportunities where work-life balance flourishes. We offer a highly competitive suite of employee benefits designed on the principles of parity and consistency. We put our people first with flexible medical, life insurance and retirement options. We also encourage employees to give back to their communities through our volunteer programs.
We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by calling +1 888 404 2494, option one.
Disclaimer:
Oracle is an Equal Employment Opportunity Employer*. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
Job Description: As an AI Engineer, you will work closely with cross-functional teams to design, build, and deploy AI solutions in a scalable and efficient manner. You will be responsible for leveraging Docker and Kubernetes for containerization and orchestration, implementing MLOps practices and utilizing your skills in python and machine learning to build and enhance our AI models. Experience in Generative AI is highly desired as we continue to push the boundaries of AI applications.
Responsibilities:
Design and develop AI/ML models and systems from prototyping to production, while ensuring scalability and efficiency.
Utilize Docker and Kubernetes for containerization, deployment and orchestration of AI models and services in production environments.
Implement and manage end-to-end MLOps pipelines to automate model training, testing, deployment and monitoring.
Build robust, reusable, and scalable Python code for AI model development and deployment.
Work on the integration and deployment of generative AI models and systems for innovative applications.
Troubleshoot, optimize and maintain production-level AI models and services.
Stay up-to-date with the latest trends and advancements in AI, machine learning and MLOps technologies.
Requirements:
Bachelor's or Master’s degree in Computer Science, Engineering or related field.
Proven experience (3+ years) in AI/ML engineering with a strong focus on Docker, Kubernetes, and MLOps.
Expertise in Python and frameworks/libraries such as TensorFlow, PyTorch, Scikit-learn or similar.
Solid understanding of machine learning algorithms and techniques, particularly in deep learning and natural language processing (NLP).
Hands-on experience deploying and managing AI models in production using Docker and Kubernetes.
Knowledge of cloud platforms and how they relate to containerized AI deployments.
Experience with CI/CD pipelines and version control (Git).
Strong understanding of generative AI models such as GANs, VAEs or transformers.
Familiarity with monitoring, logging, and debugging AI/ML systems in production environments.
Excellent communication and teamwork skills, with the ability to collaborate with diverse teams.
Preferred Qualifications:
Experience with large-scale AI model deployments.
Knowledge of additional languages such as Java, Go or C++.
Familiarity with data engineering tools and frameworks (Apache Kafka, Spark etc.).
Exposure to AI ethics and governance.
Career Level - IC3
Responsibilities
Job Description: As an AI Engineer, you will work closely with cross-functional teams to design, build, and deploy AI solutions in a scalable and efficient manner. You will be responsible for leveraging Docker and Kubernetes for containerization and orchestration, implementing MLOps practices and utilizing your skills in python and machine learning to build and enhance our AI models. Experience in Generative AI is highly desired as we continue to push the boundaries of AI applications.
Responsibilities:
Design and develop AI/ML models and systems from prototyping to production, while ensuring scalability and efficiency.
Utilize Docker and Kubernetes for containerization, deployment and orchestration of AI models and services in production environments.
Implement and manage end-to-end MLOps pipelines to automate model training, testing, deployment and monitoring.
Build robust, reusable, and scalable Python code for AI model development and deployment.
Work on the integration and deployment of generative AI models and systems for innovative applications.
Troubleshoot, optimize and maintain production-level AI models and services.
Stay up-to-date with the latest trends and advancements in AI, machine learning and MLOps technologies.
Requirements:
Bachelor's or Master’s degree in Computer Science, Engineering or related field.
Proven experience (3+ years) in AI/ML engineering with a strong focus on Docker, Kubernetes, and MLOps.
Expertise in Python and frameworks/libraries such as TensorFlow, PyTorch, Scikit-learn or similar.
Solid understanding of machine learning algorithms and techniques, particularly in deep learning and natural language processing (NLP).
Hands-on experience deploying and managing AI models in production using Docker and Kubernetes.
Knowledge of cloud platforms and how they relate to containerized AI deployments.
Experience with CI/CD pipelines and version control (Git).
Strong understanding of generative AI models such as GANs, VAEs or transformers.
Familiarity with monitoring, logging, and debugging AI/ML systems in production environments.
Excellent communication and teamwork skills, with the ability to collaborate with diverse teams.
Preferred Qualifications:
Experience with large-scale AI model deployments.
Knowledge of additional languages such as Java, Go or C++.
Familiarity with data engineering tools and frameworks (Apache Kafka, Spark etc.).
Exposure to AI ethics and governance.
Diversity & Inclusion:
An Oracle career can span industries, roles, Countries and cultures, giving you the opportunity to flourish in new roles and innovate, while blending work life in. Oracle has thrived through 40+ years of change by innovating and operating with integrity while delivering for the top companies in almost every industry.
In order to nurture the talent that makes this happen, we are committed to an inclusive culture that celebrates and values diverse insights and perspectives, a workforce that inspires thought leadership and innovation. .
Oracle offers a highly competitive suite of Employee Benefits designed on the principles of parity, consistency, and affordability. The overall package includes certain core elements such as Medical, Life Insurance, access to Retirement Planning, and much more. We also encourage our employees to engage in the culture of giving back to the communities where we live and do business.
At Oracle, we believe that innovation starts with diversity and inclusion and to create the future we need talent from various backgrounds, perspectives, and abilities. We ensure that individuals with disabilities are provided reasonable accommodation to successfully participate in the job application, interview process, and in potential roles. to perform crucial job functions.
That’s why we’re committed to creating a workforce where all individuals can do their best work. It’s when everyone’s voice is heard and valued that we’re inspired to go beyond what’s been done before.
About Us
As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s problems. True innovation starts with diverse perspectives and various abilities and backgrounds.
When everyone’s voice is heard, we’re inspired to go beyond what’s been done before. It’s why we’re committed to expanding our inclusive workforce that promotes diverse insights and perspectives.
We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity.
Oracle careers open the door to global opportunities where work-life balance flourishes. We offer a highly competitive suite of employee benefits designed on the principles of parity and consistency. We put our people first with flexible medical, life insurance and retirement options. We also encourage employees to give back to their communities through our volunteer programs.
We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by calling +1 888 404 2494, option one.
Disclaimer:
Oracle is an Equal Employment Opportunity Employer*. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
- Which includes being a United States Affirmative Action Employer
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