Associate Director, MLOps Engineering

PathAI; Boston (MA); Hybrid; USD 182,000 - 278,000; Full time

Job summary

PathAI in Boston is seeking an Associate Director, MLOps Lead to guide the team building our ML infrastructure and production pipelines. You will oversee high-scale AI training and inference workloads, cloud infra, Kubernetes, observability, and IaC practices across global deployments.

The role emphasizes design for reliability, collaboration, and continuous improvement, with a hybrid work model in Boston and a strong focus on evolving the ML stack to meet scale and performance goals.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent).
• 8–10+ years in Software/ML Engineering with 4+ years managing teams and platform strategy.
• Experience building production-grade MLOps or ML infrastructure frameworks.
• Proven track record growing engineering teams, managing budgets and driving MLOps adoption.

Responsibilities

• Vision and roadmap for the MLOps team to support ML development and deployment needs.
• Lead and mentor a team of 6-7+ engineers and allocate resources for ongoing services and strategic initiatives.
• Collaborate with ML, data science, product, engineering, and infrastructure to deploy new solutions.
• Architect compute and storage pipelines for millions of slides and artifacts without fragmentation.
• Modernize the AI product inference stack for 5-10x growth across global deployments.
• Work with SRE to establish metrics for utilization, bottlenecks, cost and turnaround time.
• Conduct Build vs. Buy assessments and Stack Refresh audits for future needs.

Skills

Kubernetes

Cloud platforms

Workflow orchestration

DevOps

Infrastructure as code

Petabyte-scale data

Production inference

ML workloads

Education

Bachelor's or Master's in CS/Engineering

Tools

Airflow

Kubeflow

Terraform

Helm

PyTorch

Scikit-learn

Databricks

Job description

Our team is passionate about solving big challenges in healthcare and transforming the field of pathology with artificial intelligence.

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.

We are seeking an Associate Director, MLOps Lead to join our Machine Learning team. In this position, you will lead the team who is responsible for the backbone of our AI/ML Stack. This is a highly visible role as you will oversee the infrastructure that bridges ML research and massive-scale production. Your primary directive is to evolve our stack to meet the next scale of needs in large scale ML training & inference workloads.

The Associate Director MLOps Lead is someone who enjoys designing and building for reliability, relishes collaboration and technical challenges, and takes pride in making things better.. Our technical space is broad: high-scale AI training & inference workloads, cloud infrastructure, Kubernetes, observability, distributed systems, and a bit of everything in between.

The Opportunity:

This role is critical for driving the scalability and efficiency of our Machine Learning Operations platform with high-impact & high growth strategic initiatives.

• Vision and Roadmap: Develop and execute the long term vision & roadmap for MLOPs team to support ML development and deployment needs across the business units. Successfully manage the tension between short-term tactical deliveries and long-term architectural transformation for future growth.
• Team Management: Lead and mentor a team of 6-7+ high-performing engineers. Strategically allocate resources to manage support for existing services while executing key strategic initiatives.
• Cross-Functional Collaboration: Partner with leaders across machine learning, data science, product engineering, and infrastructure to proactively identify pain points, address bottlenecks, and facilitate the deployment of new solutions.
• Foundation Model Readiness: Architect the compute and storage pipelines required for ML Engineers to manage millions of slides and complex derived artifacts without data fragmentation or synchronization latency.
• Inference Modernization: Modernize the AI Product inference stack to support 5-10x growth of AI runs across global deployments.
• System Observability: Collaborate with Site Reliability Engineering (SRE) to establish comprehensive metrics covering compute under-utilization, network bottlenecks, and granular cost and turn-around-time attribution.
• Technology Refresh: Conduct "Build vs. Buy" assessments, leading "Stack Refresh" audits to benchmark our proprietary tools against best-in-class commercial and open-source alternatives to meet our future needs.

Who You Are:
(Required)

• You have a Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience).
• You have 8–10+ years in Software/ML Engineering, with 4+ years managing engineering teams and platform strategy; experience building production-grade frameworks for MLOps or ML Infrastructure.
• You have a proven track record of growing engineering teams, managing team budgets/cloud costs, and driving MLOps platform adoption across multi-disciplinary organization units.
• You have a demonstrated level of deep technical expertise with ML workloads on kubernetes, cloud computing platforms (AWS/GCP/Azure), workflow orchestration (Airflow, Kubeflow, or proprietary equivalents) and DevOps principles and infrastructure-as-code (Helm, Terraform).
• You have demonstrated experience managing petabyte-scale datasets and high-throughput production inference pipelines.
• You have demonstrated strong software engineering skills in complex, multi-language systems and experience with scalable service architecture.
• You have experience using AI assistants (e.g. CoPilot, Cursor, Claude) across platform development lifecycles.

Preferred:

• You have experience working with ML frameworks like PyTorch or Scikit-learn.
• You have experience with large-scale data processing frameworks (e.g. Spark, Hive, Databricks, Amazon EMR)
• You have demonstrated expertise in MLOps principles, including model lifecycle management, feature stores, model monitoring, and CI/CD for ML.
• You have a familiarity with security and compliance best practices in ML systems.

This is a hybrid position based in Boston, MA.
Relocation benefits are not available for this position.

The expected salary range for this position based on the primary location Boston, MA is $181,500 - $278,300. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law.

PathAI is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications — that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way.