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 vision and roadmap for the MLOps team across business units.
  • Lead and mentor a team of 6-7+ engineers while balancing service support and strategic initiatives.
  • Partner with machine learning, data science, product engineering, and infrastructure leaders to identify bottlenecks and deploy new solutions.
  • Architect compute and storage pipelines that support millions of slides and complex derived artifacts at scale.
  • Modernize the AI product inference stack to support 5-10x growth in global AI runs.
  • Work with SRE to define observability metrics for compute utilization, network bottlenecks, cost, 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 machine learning operations platform.

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.
  • Experience building production-grade frameworks for MLOps or ML infrastructure.
  • Deep technical expertise 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 DevOps principles and infrastructure-as-code 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 such as PyTorch or Scikit-learn (preferred).
  • Experience with large-scale data processing frameworks such as Spark, Hive, Databricks, or Amazon EMR (preferred).
  • Experience with 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 pay 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.

Interested in this position?

Apply directly on the company website

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