HPC & MLaaS Containerization Engineer

We are seeking a highly experienced HPC & MLaaS Containerization Engineer to architect, deploy, and optimize containerized workloads across high-performance computing (HPC) and Machine Learning as a Service (MLaaS) environments.
This role requires deep expertise in container orchestration, GPU-aware scheduling, HPC workload management, and enterprise-grade automation. The ideal candidate understands the intersection of traditional HPC schedulers (e.g., PBS) with modern container platforms (Docker/Mirantis Kubernetes Engine) and can operationalize scalable, secure, high-throughput compute environments.
This role requires deep expertise in container orchestration, GPU-aware scheduling, HPC workload management, and enterprise-grade automation. The ideal candidate understands the intersection of traditional HPC schedulers (e.g., PBS) with modern container platforms (Docker/Mirantis Kubernetes Engine) and can operationalize scalable, secure, high-throughput compute environments.
This role requires deep expertise in container orchestration, GPU-aware scheduling, HPC workload management, and enterprise-grade automation. The ideal candidate understands the intersection of traditional HPC schedulers (e.g., PBS) with modern container platforms (Docker/Mirantis Kubernetes Engine) and can operationalize scalable, secure, high-throughput compute environments.
This role requires deep expertise in container orchestration, GPU-aware scheduling, HPC workload management, and enterprise-grade automation. The ideal candidate understands the intersection of traditional HPC schedulers (e.g., PBS) with modern container platforms (Docker/Mirantis Kubernetes Engine) and can operationalize scalable, secure, high-throughput compute environments.

Pay rate: 50 - 75/hr based on experience

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Familiarity with Slurm in addition to PBS (conceptual or operational).
Experience with VMware / vSphere, particularly in environments where virtualization supports HPC or ML workflows.
Exposure to secure container registries (e.g., Docker registries with access controls, scanning, and promotion workflows).
Experience supporting or building MLaaS (Machine Learning as a Service) platforms or self‑service research environments.
Prior work in highly customized, institutionalized systems with significant in‑house tooling.
Experience patching and maintaining underlying host systems supporting container platforms.
Ability to design or advocate for dedicated research environments to improve user productivity.
Experience working in organizations without formal architects or data scientists, helping mature platforms organically.
Familiarity with documentation standards and platform enablement for research or engineering users.

Located in/around Niskayuna, NY

Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.