Senior Machine Learning Infrastructure Engineer

April 16

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Description

• As a Senior Machine Learning Infrastructure Engineer, you'll lead the design, development, and optimization of our machine learning infrastructure. You'll work on challenging projects, from building scalable data pipelines to deploying and managing machine learning models in production environments. If you're a seasoned engineer with expertise in machine learning infrastructure technologies and a passion for building scalable, reliable, and efficient systems, 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 infrastructure engineering, with a focus on machine learning infrastructure. • Proficiency in cloud platforms such as AWS, Azure, or Google Cloud Platform, and services like AWS SageMaker, Azure Machine Learning, or Google AI Platform. • Strong programming skills in languages such as Python, Java, or Scala, with experience in distributed computing frameworks like Apache Spark or TensorFlow. • Experience with containerization technologies such as Docker and container orchestration platforms such as Kubernetes. • Strong understanding of machine learning concepts and techniques, with experience deploying and managing machine learning models in production environments. • Strong problem-solving skills and analytical thinking, with the ability to design and troubleshoot complex infrastructure issues. • 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 Machine Learning Infrastructure Engineers typically ranges from $170,000 to $230,000 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 AI-driven innovation.