Job Summary

Global MNC Tech is seeking a highly skilled MLOps Engineer – Production Infrastructure to join our dynamic AI and Machine Learning team. This role is pivotal in designing, deploying, and managing robust, scalable, and secure production pipelines for machine learning models. The ideal candidate will bridge the gap between data science and engineering, ensuring ML models are efficiently deployed, monitored, and maintained in production environments. This position offers the opportunity to work with cutting-edge AI technologies in a global, fast-paced, and innovation-driven environment.

Key Responsibilities

• Design, implement, and maintain end-to-end machine learning pipelines for production environments.

• Automate model deployment, monitoring, scaling, and retraining processes.

• Collaborate with data scientists, software engineers, and DevOps teams to optimize ML workflows and production reliability.

• Ensure high availability, performance, and security of ML infrastructure.

• Implement CI/CD pipelines specifically for ML projects, integrating testing and validation of models.

• Monitor model performance and provide alerts for drift, anomalies, or degradation in production.

• Manage cloud and on-premises ML infrastructure, including Kubernetes, Docker, and serverless architectures.

• Maintain comprehensive documentation of processes, workflows, and system configurations.

Required Skills and Qualifications

• Strong experience in Python, Bash, and scripting languages for automation.

• Proficiency with MLOps frameworks such as Kubeflow, MLflow, TFX, or similar.

• Hands-on experience with cloud platforms (AWS, Azure, GCP) and associated ML services.

• Experience with containerization (Docker) and orchestration (Kubernetes).

• Knowledge of CI/CD pipelines, Git workflows, and infrastructure-as-code tools (Terraform, Ansible).

• Familiarity with monitoring, logging, and alerting tools for ML systems.

• Understanding of model versioning, data versioning, and reproducibility best practices.

Experience

• Minimum 3-5 years of experience in MLOps, DevOps for ML, or Production ML Engineering roles.

• Proven track record in deploying and maintaining ML models in production at scale.

• Experience collaborating with cross-functional teams in global organizations.

Working Hours

• Full-time role, standard office hours with flexibility to support global operations.

• Occasional on-call support for critical production issues may be required.

• Remote and hybrid options may be available depending on location.

Knowledge, Skills, and Abilities

• Strong analytical and problem-solving abilities.

• Excellent communication and collaboration skills in a multi-disciplinary, global team environment.

• Ability to handle high-pressure situations and manage multiple priorities effectively.

• Proactive in adopting new technologies and optimizing ML workflows.

• Strong understanding of software engineering best practices, version control, and agile methodologies.

Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible working arrangements and generous paid time off.

• Opportunities for professional growth, certifications, and continuous learning.

• Access to cutting-edge ML tools, cloud infrastructure, and global projects.

Why Join Global MNC Tech?

• Work at the forefront of AI and machine learning technologies in a global, innovative, and inclusive environment.

• Collaborate with world-class teams driving impact across industries.

• Opportunity to shape ML infrastructure that directly supports business-critical applications.

• Enjoy a culture that values creativity, growth, and work-life balance.

How to Apply

• Interested candidates should submit their resume/CV and a cover letter detailing relevant experience to us.

• Please include MLOps Engineer – Production Infrastructure in the subject line.

• Applications will be reviewed on a rolling basis. Shortlisted candidates will be contacted for interviews.