PathAI

PathAI

PathAI is a biomedical software company based in Boston, Massachusetts, that leverages artificial intelligence to improve patient outcomes in pathology. Their platform enhances diagnostic accuracy and treatment efficacy for diseases like cancer through...

Pharmaceuticals
251-1K
Founded 2016
$90M raised

Description

  • Develop and execute the long-term MLOps vision and roadmap to support machine learning development and deployment across business units.
  • Lead and mentor a team of 6-7+ engineers while balancing support for existing services with strategic platform initiatives.
  • Partner with machine learning, data science, product engineering, and infrastructure leaders to identify bottlenecks and deliver new solutions.
  • Design compute and storage pipelines that can support millions of slides and complex derived artifacts at scale.
  • Modernize the AI product inference stack to support 5-10x growth in AI runs across global deployments.
  • Work with Site Reliability Engineering to establish observability metrics for utilization, bottlenecks, cost attribution, and turnaround time.
  • Conduct build-versus-buy evaluations and stack refresh audits to compare internal tools with commercial and open-source alternatives.
  • Drive scalability and efficiency improvements for the MLOps platform through high-impact strategic initiatives.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
  • 2-3+ years of experience managing engineering teams, with a focus on production-grade MLOps or ML infrastructure.
  • Deep technical experience with ML workloads on Kubernetes and cloud platforms such as AWS, GCP, or Azure.
  • Experience with workflow orchestration tools such as Airflow, Kubeflow, or proprietary equivalents.
  • Experience with infrastructure-as-code and DevOps tools such as Helm and Terraform.
  • Proven experience managing petabyte-scale datasets and high-throughput production inference pipelines.
  • Strong software engineering skills in complex, multi-language systems and scalable service architecture.
  • Experience using AI assistants such as CoPilot, Cursor, or Claude across the platform development lifecycle.
  • Exposure to ML frameworks like PyTorch or Scikit-learn (preferred).
  • Experience with large-scale data processing frameworks such as Spark, Hive, Databricks, or Amazon EMR (preferred).
  • Expertise in MLOps practices including model lifecycle management, feature stores, model monitoring, and CI/CD for ML (preferred).
  • Familiarity with security and compliance best practices in ML systems (preferred).

Benefits

  • Annual base salary range of $181,500 to $278,300.
  • Eligible for equity awards.
  • Not overtime eligible.
  • Individual compensation packages are tailored based on skills, experience, qualifications, and other job-related factors.
  • Equal opportunity employer with a workplace free of harassment and discrimination.

Interested in this position?

Apply directly on the company website

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