Description:

Lead and mentor a team of ML Operations Engineers in driving MLOps innovation and execution.
Design and implement scalable infrastructure for deploying and serving machine learning models using cloud platforms and containerization technologies.
Develop automated pipelines for deploying machine learning models into production environments with consistency and reproducibility.
Implement monitoring and alerting systems to track model performance, data drift, and other metrics for proactive issue detection.
Establish version control and management processes for machine learning models to enable tracking, rollback, and experimentation.
Implement CI/CD pipelines for automating model training, testing, and deployment to reduce time to market and improve agility.
Optimize machine learning infrastructure performance and scalability using distributed computing, parallelization, and resource management techniques.
Ensure machine learning systems comply with security and privacy standards by implementing access controls and encryption.
Document MLOps processes, best practices, and standards to provide guidance and training to data scientists and engineers.
Collaborate with cross-functional teams to streamline the machine learning lifecycle and drive continuous improvement.
Stay informed about the latest advancements in MLOps tools and technologies to enhance machine learning operations.

Requirements:

Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.
7+ years of experience in software engineering, DevOps, or related roles focusing on machine learning operations infrastructure.
Leadership experience with the ability to lead and mentor engineering teams.
Strong understanding of machine learning concepts and techniques, working with data science teams and models.
Proficiency in Python, Java, or Scala, and experience with cloud platforms like AWS, Azure, or Google Cloud.
Experience with Docker, Kubernetes, TensorFlow, PyTorch, scikit-learn, MLflow, CI/CD pipelines, version control systems, and automation tools.
Strong problem-solving skills, analytical thinking, and troubleshooting abilities.
Excellent communication and collaboration skills for working in cross-functional teams.

Competitive salary ranging from $150,000 to $250,000 per year.
Comprehensive health, dental, and vision insurance plans.
Flexible work hours and remote work options.
Generous vacation and paid time off.
Professional development opportunities with access to training programs, conferences, and workshops.
State-of-the-art technology environment with cutting-edge tools and resources.
Vibrant and inclusive company culture with growth and advancement opportunities.
Exciting projects with real-world impact in MLOps innovation.