PathAI
Associate Director, MLOps Engineering
$182K–$278K
Boston (Onsite) Preferred, New York (Onsite), or Remote +2 · Remote · Director · Full-time · Posted Sep 24, 2026
- Location
- Boston (Onsite) Preferred, New York (Onsite), or Remote
Boston, Massachusetts, United States
New York, New York, United States - Experience
- 8–10+ years in Software/ML Engineering, with 4+ years managing engineering teams and platform strategy.
- Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience).
About the job
Leads the MLOps team and evolves PathAI’s infrastructure for scalable machine-learning training and inference in production.
What you'll do
- Set the MLOps team’s long-term vision and roadmap while balancing immediate delivery with architectural improvements.
- Lead and mentor 6–7+ engineers, manage resources, and collaborate across machine learning, data science, product engineering, and infrastructure.
- Modernize compute, storage, inference, and observability systems; assess build-versus-buy and technology refresh options.
What they ask for
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience).
- 8–10+ years in Software/ML Engineering, including 4+ years managing engineering teams and platform strategy; experience building production-grade MLOps or ML infrastructure frameworks.
- Experience managing petabyte-scale datasets and high-throughput production inference pipelines; strong software engineering skills in complex, multi-language systems and scalable service architecture.
- Expertise with ML workloads on Kubernetes, cloud platforms (AWS/GCP/Azure), workflow orchestration, DevOps, infrastructure-as-code, and AI assistants across platform development lifecycles.
Nice to have
- Experience with PyTorch or Scikit-learn and large-scale data processing frameworks such as Spark, Hive, Databricks, or Amazon EMR.
- Expertise in MLOps principles or familiarity with security and compliance best practices in ML systems.
Pay
$181,500 - $278,300 USD base salary
Tools
Kubernetes, AWS, GCP, Azure, Airflow, Kubeflow, Helm, Terraform
AI focus
Leads infrastructure for AI/ML training and inference, including production deployment, scaling, and readiness for foundation-model workloads; uses AI assistants in platform development.
Model-written summary · the original posting is authoritative