Strong ML Ops with (DevOps Infra) engineer- PST TIME -Remote - Role

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Overview

Sapot Systems Inc. is seeking a highly skilled Machine Learning Operations (ML Ops) Engineer with a strong background in DevOps Infrastructure to work remotely in the Pacific Standard Time (PST) zone. The successful candidate will play a crucial role in integrating machine learning into production systems, scaling ML models, and automating ML pipelines. You will collaborate with data scientists and software engineers to enhance the deployment and monitoring of machine learning systems, ensuring they meet business and operational needs effectively. This role requires a solid understanding of both machine learning and DevOps practices to streamline processes and optimize performance.

Job Responsibilities

• Design, implement, and maintain ML Ops frameworks for deploying machine learning models into production.
• Collaborate with data science teams to create automation solutions for data preprocessing, model training, and testing.
• Monitor and evaluate model performance, implementing enhancements where necessary.
• Develop CI/CD pipelines specific to ML workflows to facilitate smooth transitions from development to production.
• Ensure compliance with best practices in code and system architecture.
• Manage versioning and testing of machine learning models.
• Provide support for troubleshooting and resolving any issues related to ML models in production.
• Document and maintain architecture designs, configurations, and operational procedures.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Information Technology, or a related field.
• A minimum of 3-5 years of experience in ML Ops, DevOps, or software engineering.
• Strong proficiency in programming languages such as Python, Java, or Scala.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
• Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Familiarity with containerization technologies such as Docker and orchestration platforms like Kubernetes.
• Solid understanding of CI/CD principles and tools (e.g., Jenkins, GitLab CI/CD).
• Excellent problem-solving skills and ability to work independently in a remote setup.

Technologies & Tools

The ML Ops Engineer role at Sapot Systems Inc. utilizes a variety of advanced technologies and tools, including but not limited to machine learning frameworks (TensorFlow, PyTorch), programming languages (Python, Java), cloud computing platforms (AWS, Google Cloud, Azure), containerization (Docker), orchestration tools (Kubernetes), and continuous integration/continuous deployment (CI/CD) tools like Jenkins or GitLab CI/CD. Familiarity with monitoring and logging tools such as Prometheus, Grafana, and ELK Stack will also be beneficial for this position.

Ideal Candidates

The ideal candidate for this ML Ops Engineer position will possess not only the technical expertise required to fulfill the responsibilities but also demonstrate strong analytical thinking and a proactive approach towards problem-solving. Candidates should have a passion for embracing new technologies and a commitment to maintaining high-quality standards in their work. Excellent communication and collaboration skills are essential, as this role requires effective interaction with both technical teams and non-technical stakeholders. A self-motivated individual with a continuous learning mindset will thrive in the dynamic environment at Sapot Systems Inc.