Senior Software Engineer, MLOps

PathAI • Boston, MA

14d

About The Position

PathAI's mission is to improve patient outcomes with AI-powered pathology. Our platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine learning and artificial intelligence. We have a track record of success in deploying AI algorithms for histopathology in translational research, pathology labs and clinical trials. Rigorous science and careful analysis is critical to the success of everything we do. Our team, composed of diverse employees with a wide range of backgrounds and experiences, is passionate about solving challenging problems and making a huge impact on patient outcomes. Where You Fit As a Senior Software Engineer, MLOps , you will 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 better – without taking yourself too seriously. Our technical space is broad: cloud infrastructure, Kubernetes, high-scale workloads, observability, distributed systems, and a bit of everything in between.

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

Nice To Haves

• Exposure to ML frameworks like PyTorch or Scikit-learn
• Experience with data workflow orchestration frameworks (e.g., Airflow, Kubeflow)
• Expertise in MLOps principles , including model lifecycle management, feature stores, model monitoring, and CI/CD for ML
• Experience with streaming data processing (Kafka, Flink, or Spark Streaming)
• Familiarity with security and compliance best practices in ML systems
• Use of AI assistants (e.g. CoPilot, Cursor) in development.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 101-250 employees