Senior ML Operations Engineer (MLOps)

April 13

Unreal Staffing, Inc

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Description

• As a Senior ML Operations Engineer, you'll play a critical role in building and maintaining the infrastructure and processes that enable the deployment, monitoring, and management of machine learning models at scale. You'll work closely with data scientists, software engineers, and DevOps teams to streamline the machine learning lifecycle and ensure reliable and efficient model operations. If you're a seasoned engineer with a passion for machine learning and a track record of designing and implementing MLOps solutions, we want you on our team.

Requirements

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field. • 5+ years of experience in software engineering, DevOps, or related roles, with a focus on building and maintaining infrastructure for machine learning operations. • Strong understanding of machine learning concepts and techniques, with experience working with data science teams and machine learning models. • Proficiency in programming languages such as Python, Java, or Scala, and experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. • Experience with containerization technologies such as Docker and orchestration tools such as Kubernetes. • Familiarity with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, or MLflow. • Experience with CI/CD pipelines, version control systems, and automation tools such as Jenkins, GitLab, or CircleCI. • Strong problem-solving skills and analytical thinking, with the ability to troubleshoot complex issues and optimize system performance. • Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.

Benefits

• Competitive salary: The industry standard salary for Senior ML Operations Engineers typically ranges from $170,000 to $250,000 per year, depending on experience and qualifications. • Comprehensive health, dental, and vision insurance plans. • Flexible work hours and remote work options. • Generous vacation and paid time off. • Professional development opportunities, including access to training programs, conferences, and workshops. • State-of-the-art technology environment with access to cutting-edge tools and resources. • Vibrant and inclusive company culture with opportunities for growth and advancement. • Exciting projects with real-world impact at the forefront of MLOps innovation.