Associate Director, MLOps Engineering

Hidden Jobs; United States; Hybrid; USD 182,000 - 278,000; Full time

Benefits offered by this job

Hybrid work arrangement

Relocation not offered

Job summary

Hidden Jobs is seeking an Associate Director-level MLOps leader to oversee the infrastructure linking ML research and large-scale production within an AI-powered pathology platform. The role blends hands-on technical leadership with team management to evolve the stack for next-scale ML training and inference for clinical and research deployments.

You will build a long-term vision, mentor a 6–7+ engineer team, and collaborate with ML, data science, product engineering, and infrastructure leaders

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field, or equivalent experience.
• 8–10+ years in Software/ML Engineering with 4+ years managing engineering teams and platform strategy.
• Deep expertise with ML workloads on Kubernetes, cloud platforms, workflow orchestration, and infrastructure-as-code (Helm, Terraform).

Responsibilities

• Develop and execute the long-term vision and roadmap for the MLOps platform across business units, balancing tactical deliveries with architectural transformation.
• Lead, mentor, and allocate work for a team of 6–7+ engineers while managing budgets and cloud costs.
• Partner with ML, data science, product engineering, and infrastructure leaders to resolve bottlenecks and enable new solutions.
• Architect compute and storage pipelines for managing millions of pathology slides and complex derived artifacts.
• Modernize the inference stack to support 5–10x growth in AI runs across global deployments, in collaboration with Site Reliability Engineering.

Skills

Kubernetes

Cloud platforms

Workflow orchestration

Infrastructure as code

Petabyte-scale data

Multi-language systems

AI coding assistants

Team leadership

Budget management

Production inference

Education

Bachelor's or Master's degree in CS/Engineering or related field

Equivalent experience

Tools

Helm

Terraform

CI/CD for ML

Job description

Role overview

An Associate Director-level MLOps leadership role overseeing the infrastructure that bridges machine learning research and large-scale production within an AI-powered pathology platform. The position combines hands-on technical leadership with team management, focused on evolving the stack to support next-scale ML training and inference workloads for clinical and research deployments.

Responsibilities

• Develop and execute the long-term vision and roadmap for the MLOps platform across business units, balancing tactical deliveries with architectural transformation.
• Lead, mentor, and allocate work for a team of 6–7+ engineers while managing budgets and cloud costs.
• Partner with machine learning, data science, product engineering, and infrastructure leaders to resolve bottlenecks and enable new solutions.
• Architect compute and storage pipelines for managing millions of pathology slides and complex derived artifacts.
• Modernize the inference stack to support 5–10x growth in AI runs across global deployments, in collaboration with Site Reliability Engineering.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent experience.
• 8–10+ years in Software/ML Engineering with 4+ years managing engineering teams and platform strategy.
• Deep expertise with ML workloads on Kubernetes, cloud platforms (AWS, GCP, or Azure), workflow orchestration, and infrastructure-as-code (Helm, Terraform).
• 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 coding assistants across the platform development lifecycle.

Nice to have

• Familiarity with ML frameworks such as PyTorch or Scikit-learn.
• Experience with large-scale data processing frameworks like Spark, Hive, Databricks, or Amazon EMR.
• Demonstrated expertise in MLOps principles including model lifecycle management, feature stores, model monitoring, and CI/CD for ML.
• Familiarity with security and compliance best practices in ML systems.

Benefits and work setup

• Hybrid position based in Boston, MA; relocation benefits are not available.
• Expected salary range of $181,500–$278,300 based on experience, qualifications, geographic location, and other job-related factors.