Senior Software Engineer, PathAI

• You have a BS or Master’s in Computer Science, Computer Engineering, Software Engineering or closely related field
• You have 5+ years of software engineering experience, with a focus on building production-grade frameworks or applications
• You have strong software engineering skills in complex, multi-language systems and experience with scalable backend architecture
• You have experience with Kubernetes and cloud computing platforms (AWS preferred)
• You have experience with observability and monitoring tools (e.g., Prometheus, Grafana, Datadog)
• You have a solid understanding of DevOps principles and infrastructure-as-code (Helm, Terraform)
• You have experience owning development platforms and serving internal customers
• You have a solid level of proficiency in Python + exposure to additional languages

Desirable

• PathAI's mission is to improve patient outcomes with AI-powered pathology
• PathAI is transforming traditional pathology methods into powerful, new technologies. These innovations in pathology can help accelerate drug development, improve confidence in the accuracy of diagnosis, and get life-saving therapies to patients more quickly. At PathAI, you'll work with a diverse and talented team of people, who are dedicated to solving complex problems and making a huge impact
• We are seeking a highly skilled Senior Software Engineer (MLOps). In this position, you play a key role in designing, developing, and scaling machine learning infrastructure that powers our enterprise AI systems. You’re someone who enjoys designing and building for reliability, relishes collaboration and technical challenges, and takes pride in making things work better
• You will architect and build infrastructure and automation, in AWS and on-premises, to support ML application development and deployment
• You will drive system design and lead architectural discussions for our MLOps suite, ensuring it meets performance, security, and compliance requirements
• You will lead technical initiatives by researching, evaluating, and implementing new MLOps tools, frameworks, and best practices
• You will collaborate with machine learning engineers, data scientists, product engineering, and infrastructure teams to bridge the gap between research and production
• You will optimize ML workflows, ensuring models are efficiently and reproducibly deployed & monitored
• You will champion engineering excellence by enforcing high coding standards, conducting design reviews, and mentoring junior engineers
• You will automate ML operations, including CI/CD for ML models, feature engineering pipelines, and deployment strategies using Kubernetes, Airflow, and other orchestration tools