Senior Software Engineer, ML Ops

PathAI•Boston, MA

1d•Hybrid

About The Position

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.

Requirements

BS or Master’s in Computer Science, Computer Engineering, Software Engineering or closely related field.
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).
Solid understanding of DevOps principles and infrastructure-as-code (Helm, Terraform).
Experience owning development platforms and serving internal customers
Solid level of proficiency in Python + exposure to additional languages

Nice To Haves

Experience with 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).
Solid level of familiarity with security and compliance best practices in ML systems.
Experience using AI assistants (e.g. CoPilot, Cursor) in development.
Outstanding interpersonal, verbal, and written communication and influencing skills: have built and cultivated important relationships both inside and outside of the organization and externally; have proven abilities to influence internal partners and stakeholders, thought leaders, national advocacy organizations, national standard-setting bodies, and other relevant external parties.
Strong analytical and critical thinking skills with attention to detail; you have the ability to manage multiple projects and drive results in a fast-paced environment; you have a collaborative mindset with demonstrated leadership capabilities.

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.