Description:

Design and architect scalable and reliable infrastructure solutions for machine learning model development, training, and deployment.
Develop and maintain infrastructure for model training and experimentation, including distributed computing environments and GPU clusters.
Implement and manage infrastructure for deploying and serving machine learning models in production environments with low-latency and high availability.
Develop monitoring and management tools for tracking model performance, health, and drift, and automate model retraining and redeployment.
Develop pipelines and tools for data processing, feature engineering, and preprocessing to support machine learning model development.
Implement infrastructure automation and orchestration using tools like Kubernetes, Docker, Terraform, and Ansible.
Optimize infrastructure performance for speed, scalability, and cost-effectiveness using cloud services and distributed computing technologies.
Implement security controls and compliance measures to protect sensitive data and ensure regulatory compliance in machine learning workflows.

Requirements:

Bachelor's degree or higher in Computer Science, Engineering, or related field.
Strong background in infrastructure engineering with hands-on experience in designing, building, and optimizing infrastructure solutions for machine learning.
Proficiency in programming languages like Python, Java, or Go, and experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
Experience with cloud platforms like AWS, Google Cloud Platform, or Microsoft Azure, and familiarity with cloud services for machine learning.
Knowledge of distributed computing technologies like Apache Spark, Hadoop, or Dask, and experience with containerization and orchestration technologies such as Docker and Kubernetes.
Strong problem-solving abilities, analytical thinking, attention to detail, and a passion for tackling complex technical challenges.
Excellent communication and collaboration skills to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.

Competitive salary ranging from $150,000 to $230,000 per year, with potential for higher compensation for exceptional candidates.
Comprehensive health, dental, and vision insurance plans.
Flexible work hours and remote work options.
Generous vacation and paid time off.
Professional development opportunities including 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 team-building activities and social events.
Opportunities for career growth and advancement within the company.
Exciting projects with real-world impact in artificial intelligence and machine learning.
Chance to work alongside top talent and industry experts in machine learning infrastructure.