Senior MLOps Engineer with DevOps

Job Summary:
We are seeking an experienced and dynamic Senior MLOps Engineer with a strong focus on DevOps and expertise in scaling AI solutions. The ideal candidate will have a robust background in designing, implementing, and optimizing CI/CD pipelines, as well as deploying and managing machine learning models in production environments. You will play a critical role in ensuring the reliability, scalability, and efficiency of AI systems across diverse platforms.
Required Skills and Experience:

• 6-8 years of hands-on experience in DevOps engineering, with a strong focus on automation and infrastructure.
• Proven expertise in MLOps, including experience with ML model deployment, monitoring, and lifecycle management.
• Deploy, monitor, and optimize machine learning models at scale using tools such as Kubeflow, MLflow, or TensorFlow Extended (TFX).
• Experience with cloud platforms such as AWS, Azure, or GCP, and container orchestration tools like Kubernetes.
• Strong programming skills in Python, Bash, or similar languages.
• Familiarity with version control systems (e.g., Git) and CI/CD tools (e.g., Jenkins, GitLab CI/CD).
• Proficiency in infrastructure-as-code tools such as Terraform or CloudFormation.
• Solid understanding of scalable architecture principles and distributed systems.
• Develop infrastructure to support large-scale AI and data processing systems.
• Work on distributed computing systems and implement strategies for efficient scaling of AI workloads.
• Optimize system performance to meet demanding AI/ML processing requirements.