About the Role:

In this role, you will be responsible for driving the execution of crucial infrastructure and platform initiatives related to AI/ML pipelines. These pipelines are designed for highly efficient and scalable model Training, & Inference. The responsibilities include building and developing tools, automation of redundant tasks, and CI/CD systems. This role requires someone with a strong collaborative and growth mindset. You will also look after the career development of the engineering team members.

What You'll Do:

• Design, develop and deploy MLOps infrastructure for to improve the velocity of development and deployment of AI and deep learning models: CI/CD, input data unit and statistical testing, experiment tracking, model registry, and monitoring and alerting of production features
• Design, develop and deploy scalable cloud AI/ML pipelines for customer-facing inference and visualization services
• Develop, implement and administer best MLOps practices relating to model development automation, evaluation, testing and deployment
• Focus on addressing availability issues, work on scaling pipelines, and improving features while maintaining SLAs on performance, reliability, and system availability
• Work with technical leads and managers to understand project requirements and business needs and collaborate with engineers across teams to identify and deliver features, services & pipelines
• Collaborate with cross-functional teams such as Backend, Frontend, and Platform to ensure the development and delivery of end-to-end product features, and robust and scalable AI pipelines
• Mentor junior team members

What We're Looking For:

• Bachelor’s Degree in Computer Science, Electrical Engineering, or related field.
• 4+ years experience in designing, implementing, and operating scalable software systems and services
• 4+ years hands-on experience with MLOps and DevOps tools (e.g., Docker, Kubernetes, Kubeflow, Spark, Airflow, AWS, CI/CD)
• Solid CS foundations including in data structures, algorithms and software engineering
• Excellent verbal and written communication skills.
• You collaborate effectively with other teams and communicate clearly about your work.
• Knowledge of one or more of computer vision, deep learning, machine learning, or statistical and predictive modeling is a strong plus