# Associate Director, MLOps Engineering
**Company:** [PathAI](https://hotfix.jobs/companies/pathai)
**Location:** Boston, MA, New York, NY
**Salary:** $182K-$278K
**Skills:** Kubernetes, AWS, GCP, Azure, Airflow, Kubeflow, Helm, Terraform, PyTorch, scikit-learn, Spark, Databricks, MLOps
**Posted:** 2026-04-22
> Leads MLOps team to build scalable ML infrastructure, manage engineering resources, and drive roadmap for ML deployment. Requires 2+ years managing teams, expertise in Kubernetes, cloud platforms, and ML workflows; bachelor's/master's degree preferred.
## Job Description
## What You’ll Do

- **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.

## What You Bring

**Required:**
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience).
- 2-3+ years of experience managing engineering team(s), with a focus on building production-grade frameworks for MLOps or ML Infrastructure.
- Deep technical expertise with ML workloads on **Kubernetes**, cloud computing platforms (**AWS**, **GCP**, **Azure**), workflow orchestration (**Airflow**, **Kubeflow**), and DevOps principles and infrastructure-as-code (**Helm**, **Terraform**).
- Proven experience managing petabyte-scale datasets and high-throughput production inference pipelines.
- Strong software engineering skills in complex, multi-language systems and experience with scalable service architecture.
- Use of AI assistants (e.g. **CoPilot**, **Cursor**, **Claude**) across platform development lifecycle.

**Nice-to-Haves:**
- Exposure to ML frameworks like **PyTorch** or **Scikit-learn**.
- Experience with large-scale data processing frameworks (e.g. **Spark**, **Hive**, **Databricks**, **Amazon EMR**).
- 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.

## Compensation
**Annual Pay Range**: $181,500 - $278,300  
Not Overtime Eligible  
Eligible for Equity
**Apply:** https://hotfix.jobs/jobs/associate-director-mlops-engineering-at-pathai-9c7cb447-6c1b-4724-8018-439518f5de9b
**Canonical:** https://hotfix.jobs/jobs/associate-director-mlops-engineering-at-pathai-9c7cb447-6c1b-4724-8018-439518f5de9b