Senior Software Engineer designing and developing MLOps infrastructure for AI pathology at PathAI. Collaborating with teams to optimize ML workflows and automate operations.
Responsibilities
Architect and build infrastructure and automation, in AWS and on-premises, to support ML application development and deployment
Drive system design and lead architectural discussions for our MLOps suite, ensuring it meets performance, security, and compliance requirements
Lead technical initiatives by researching, evaluating, and implementing new MLOps tools, frameworks, and best practices
Collaborate with machine learning engineers, data scientists, product engineering, and infrastructure teams to bridge the gap between research and production
Optimize ML workflows, ensuring models are efficiently and reproducibly deployed & monitored
Champion engineering excellence by enforcing high coding standards, conducting design reviews, and mentoring junior engineers
Automate ML operations, including CI/CD for ML models, feature engineering pipelines, and deployment strategies using Kubernetes, Airflow, and other orchestration tools.
Requirements
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
5+ years of software engineering experience, with a focus on building production-grade frameworks or applications
Strong software engineering skills in complex, multi-language systems and experience with scalable backend architecture
Experience with Kubernetes and cloud computing platforms (AWS preferred)
Experience with observability and monitoring tools (e.g., Prometheus, Grafana, Datadog)
Understanding of DevOps principles and infrastructure-as-code (Helm, Terraform)
Experience owning development platforms and serving internal customers
Proficiency in Python + exposure to additional languages
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