SSMLOPS7326

Job Openings

Title: MLOps Engineer Job Code: SSMLOPS7326 Location : New Jersey / Remote Job Description:

The MLOps Engineer will be responsible for building and maintaining the infrastructure and pipelines required to operationalize machine learning (ML) models at scale. This role will focus on enabling seamless integration, deployment, monitoring, and management of ML models in production environments. The MLOps Engineer will collaborate with data scientists, software engineers, and DevOps teams to ensure the reliability and scalability of AI/ML solutions. Responsibilities:

• Design and implement MLOps pipelines for model training, deployment, and monitoring using tools like MLflow, Kubeflow, and TFX.
• Automate the end-to-end ML lifecycle, including data ingestion, model training, validation, and deployment.
• Collaborate with data scientists to containerize and deploy ML models using Docker and Kubernetes.
• Monitor and optimize the performance of ML models in production environments.
• Implement CI/CD pipelines for ML models to ensure continuous integration and delivery.
• Ensure compliance with data governance and model explainability requirements.
• Stay updated with emerging trends in MLOps, AI infrastructure, and cloud-native technologies.

Qualifications: Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field. Experience:

• 4-7 years of experience in MLOps, DevOps, or data engineering.
• Proficiency in MLOps tools like MLflow, Kubeflow, and TFX.
• Strong programming skills in Python, Bash, or Go.
• Hands-on experience with cloud platforms like AWS SageMaker, Azure ML, or GCP Vertex AI.
• Familiarity with containerization tools like Docker and orchestration tools like Kubernetes.
• Excellent problem-solving and communication skills.