Associate Director, MLOps Engineering

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.