Software Engineering Co-op MLOps: September

About the role

PathAI is seeking a student for a co-op position starting in September to support our machine learning operations infrastructure. You will contribute to the development and maintenance of systems that power our pathology AI products. In this capacity, you will own the reliability and performance of the internal tools used by data scientists and researchers. The hire will be responsible for ensuring that model deployment pipelines are robust, observable, and efficient. You will work closely with cross-functional teams to translate operational needs into technical solutions. This role provides a foundational opportunity to learn how AI products move from experimentation to production at scale. Your contributions will directly impact the speed and quality of our software delivery lifecycle.

Key facts

What you'll do

• Build and refine pipelines for machine learning model deployment and monitoring.
• Collaborate with engineers to improve the scalability of our data processing workflows.
• Assist in maintaining the infrastructure that supports our digital pathology platforms.
• Troubleshoot technical issues within the development and production environments.
• Implement logging and metrics collection to enhance visibility into system behavior.
• Support the configuration and management of cloud-based infrastructure resources.
• Automate routine operational tasks to reduce manual effort and potential for error.
• Participate in code reviews to ensure adherence to best practices and standards.
• Help document procedures and architectures to support long-term maintainability.
• Work with containerization technologies to package and deploy applications consistently.

Requirements

• Current enrollment in a degree program related to computer science, software engineering, or a related technical field.
• Experience with software development practices and version control systems.
• Ability to commit to a co-op term beginning in September.
• Strong problem-solving skills and attention to detail in operational contexts.
• Willingness to learn and apply new tools and technologies as needed for the role.
• Effective communication skills to collaborate with technical and non-technical stakeholders.
• A proactive approach to identifying issues and proposing improvements to workflows.
• Commitment to working within a structured team environment that follows established processes.

Skills & tools

• Proficiency in programming languages commonly used in MLOps.
• Familiarity with cloud computing platforms and containerization technologies.
• Understanding of machine learning lifecycle management.
• Experience with scripting and automation to streamline operational tasks.
• Knowledge of monitoring and observability tools for distributed systems.
• Exposure to data processing frameworks and pipeline orchestration tools.
• Basic understanding of how models are trained, validated, and served in production.
• Familiarity with infrastructure as code principles to manage environment consistency.

Practical notes

• This role is based in our Boston office. Please ensure your application includes your availability for the September start date.
• The engagement is structured as a co-op position with defined start and end points.
• Applicants must be eligible to work in the United States without sponsorship for this opportunity.
• Travel to the Boston office will be required on a regular basis during the assignment.
• Candidates should align their schedules to meet the demands of the September start date.
• No partial remote arrangements are available for this specific co-op role.
• Early communication regarding start date feasibility is strongly encouraged.

This co-op opportunity at PathAI places you at the intersection of software engineering and machine learning operations. You will gain hands-on experience with the tools and practices that enable reliable AI deployments. The position is ideal for a student looking to apply academic knowledge to real-world engineering challenges. You will see how theoretical concepts in computer science translate into production systems that handle complex data. The role emphasizes collaboration, requiring interaction with both technical teams and stakeholders. You will develop a strong understanding of how to maintain infrastructure that supports critical business functions. The skills acquired will be valuable for future careers in MLOps, platform engineering, or data infrastructure. This is a chance to build a professional foundation while contributing to impactful healthcare technology.