Machine Learning Operations Engineer

About Knowdis.ai

Knowdis.ai is an AI-first company specializing in e-commerce applications. We harness the power of Machine Learning and AI to enhance e-commerce operations, optimize customer experiences, and drive growth. If you are passionate about AI-driven product innovation, this is the perfect opportunity to make a meaningful impact.

Key Responsibilities

• Infrastructure Management: Build scalable and robust infrastructure for Machine Learning models, ensuring seamless production integration
• CI/CD Expertise: Develop and maintain CI/CD pipelines with a focus on ML model deployment
• Model Deployment and Monitoring: Deploy ML models using TensorFlow Serving, Pytorch Serving, Triton Inference Server, or TensorRT and monitor their performance in production
• Collaboration: Work closely with data scientists and software engineers to transition ML models from research to production
• Security and Compliance: Uphold security protocols and ensure regulatory compliance in ML systems

Skills and Experience Required

• Proficiency in Docker and Kubernetes for containerization and orchestration
• Experience with CI/CD pipeline development and maintenance
• Experience in deploying ML models using TensorFlow Serving, Pytorch Serving, Triton Inference Server, and TensorRT
• Experience with cloud platforms like AWS, Azure, and GCP
• Strong problem-solving, communication, and teamwork skills

Qualifications

• Bachelor’s/Master’s degree in Computer Science, Engineering, or a related field
• 4-6 years of experience in ML project management, with a recent focus on MLOps

Additional Competencies

• AI Technologies Deployment, Data Engineering, IT Performance, Scalability Testing, and Security Practices.

SELECTION PROCESS

1. Interested Candidates are mandatorily required to apply through this listing on Jigya. Only applications received through Jigya will be evaluated further
2. Shortlisted candidates may be required to appear in an Online Assessment administered by Jigya on behalf of the Client
3. Candidates selected after the screening test will be interviewed by the Client