The ML Engineer will be responsible for designing, implementing, and maintaining machine learning infrastructure, pipelines, and workflows. This role will require a deep understanding of data management, software development, and cloud computing. The successful candidate will work closely with data scientists, software engineers, and other stakeholders to ensure that machine learning models are deployed, monitored, and updated efficiently and effectively.

Job Description:

• Develop, deploy and maintain machine learning models, pipelines and workflows in production environment.

• Build and maintain machine learning infrastructure that is scalable, reliable and efficient.

  • Collaborate with data scientists and software engineers to design and implement machine learning         workflows.

• Implement monitoring and logging tools to ensure that machine learning models are performing optimally.

• Continuously improve the performance, scalability and reliability of machine learning systems.

• Work with DevOps team to deploy and manage infrastructure for machine learning services.

• Create and maintain technical documentation for machine learning infrastructure and workflows.

• Stay up to date with the latest developments in machine learning and cloud computing technologies. 

Qualifications Required Skills:

• Bachelor's or Master's degree in computer science, engineering or related field.

 • 2+ years of experience in software development, machine learning engineering or related field.

• Strong understanding ofmachine learning concepts and frameworks, including TensorFlow, PyTorch,Scikit-learn, etc.

• Experience in AWS Cloud,S3, EKS, ECT, Ec2, IAM Services

• Experience with DevOpspractices and tools such as Kubernetes, Docker, Jenkins, Git.

• Experience in developingand deploying machine learning models in a production environment.

• Strong analytical and problem-solving skills Preferred Skills

• Familiarity with database technologies such as SQL, NoSQL, JDBC

• LLMs and GENAI Experience