Description:
Motive is looking for an MLOps Engineer to drive infrastructure and platform initiatives for AI/ML pipelines. This role focuses on building scalable and efficient AI model training and inference pipelines, along with automation and CI/CD implementation. The ideal candidate should have a strong collaborative mindset and be capable of mentoring junior engineers while ensuring the reliability and scalability of AI services.
Responsibilities:
- Develop and deploy MLOps infrastructure to enhance model training and inference capabilities.
- Implement CI/CD pipelines, experiment tracking, model registry, and monitoring systems for AI models.
- Design and optimize scalable AI/ML cloud pipelines for real-time inference and data visualization.
- Automate repetitive tasks and improve AI system performance, reliability, and scalability.
- Work with technical leads and engineers to understand project requirements and collaborate across teams.
- Ensure best MLOps practices for model development automation, testing, and deployment.
- Mentor junior engineers and contribute to their career development.
Requirements:
- Bachelor’s Degree in Computer Science, Electrical Engineering, or a related field.
- 3+ years of experience in designing and operating scalable software systems and AI pipelines.
- Strong expertise in MLOps and DevOps tools (e.g., Docker, Kubernetes, Kubeflow, Spark, Airflow, AWS, CI/CD).
- Solid data structures, algorithms, and software engineering knowledge.
- Excellent communication and collaboration skills.
- Knowledge in AI/ML, computer vision, deep learning, or predictive modeling is a plus.