Senior / Staff Machine Learning Ops Engineer

Role Description

You will:

• Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models.
• Collaborate with data scientists and engineers to understand model requirements and optimize pipeline processes.
• Automate the training, testing and deployment processes for machine learning models.
• Continuously monitor and maintain model pipelines, ensuring optimal performance, accuracy and reliability.
• Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.
• Ensure compliance with security and data privacy standards in all MLOps activities.

Qualifications

• 3-5 years of experience in MLOps, DevOps or a related field.
• Bachelor’s degree in Computer Science, Data Science or a related field.
• Strong understanding of machine learning principles and model lifecycle management.
• Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow or PyTorch.
• Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning services.
• Familiarity with containerization and orchestration tools such as Kubernetes and Docker.
• Knowledge of CI/CD pipelines, automation tools and version control systems like Git.
• Strong problem-solving skills and ability to troubleshoot complex issues.
• Experience with monitoring tools and practices for model performance in production.
• Ability to work collaboratively in cross-functional teams.

Requirements

• Bonus/nice to have:
• Experience with infrastructure-as-code (IaC) tools such as Terraform or Crossplane.
• Knowledge of big data technologies like Apache Spark or Hadoop.
• Familiarity with data engineering practices and tools.
• Experience with A/B testing and model validation in production environments.
• Relevant MLOps certifications (e.g., AWS Certified Machine Learning – Specialty, DataRobot MLOps Certification) are a plus.

Benefits

• Competitive compensation and equity awards.
• Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
• Unlimited Vacation.
• Flexible hours and Work from Home support.
• Daily drinks, snacks and catered meals (when in office).
• Regularly scheduled team building activities and social events both on-site, off-site & virtually.
• As we grow, this list continues to evolve!