Job Openings Manager, AI & Research Computing Initiatives

About the job Manager, AI & Research Computing Initiatives

Manager, AI & Research Computing Initiatives

Job ID: 3743
Client: Boston University
Location: Boston, MA
Duration: 9-Month Contract
Work Arrangement: Hybrid – Must be local to Boston, MA
Schedule: 40 Hours per Week
Industry: Higher Education / Artificial Intelligence / Research Computing

Job Overview

Sigma Inc. is seeking an experienced Manager, AI & Research Computing Initiatives for a 9-month contract opportunity supporting Boston University in Boston, MA.

This leadership position will drive the strategy, planning, and development of artificial intelligence infrastructure and research computing initiatives. The ideal candidate will have a strong background in AI/ML infrastructure, High-Performance Computing (HPC), GPU computing, cloud infrastructure, MLOps, and technical team management.

The Manager will lead the technical roadmap for AI-enabled research computing, anticipate emerging infrastructure requirements, and collaborate with faculty, researchers, academic departments, and IT leadership to develop scalable solutions supporting AI-intensive research projects.

This role combines technical strategy, AI infrastructure planning, research computing operations, project coordination, and people management. The successful candidate will serve as a technical leader and subject matter expert, helping advance AI and machine learning capabilities across the university's research environment.

Candidates must be local to the Boston, MA area and available to work in a hybrid arrangement.

Key Responsibilities

AI Research Computing Strategy & Infrastructure

  • Develop and drive the technical roadmap for AI-enabled research computing and infrastructure.
  • Lead planning and capacity management for GPU computing, accelerators, and high-performance computing resources.
  • Evaluate and recommend AI/ML infrastructure, containerized computing environments, and MLOps tools.
  • Anticipate emerging requirements related to AI workloads, data pipelines, model training, and model-serving infrastructure.
  • Provide technical guidance and expertise on AI infrastructure, research computing, and emerging AI technologies.
  • Collaborate with research computing leadership to develop AI/ML strategies and infrastructure plans.
  • Research emerging technologies, industry standards, and best practices in artificial intelligence and automation.

Project & Service Coordination

  • Coordinate daily research computing projects, service requests, and incident management activities.
  • Monitor service delivery, identify potential delays, and escalate critical issues to leadership.
  • Coordinate cross-functional activities between research computing teams, IT infrastructure groups, and academic research departments.
  • Ensure researchers receive appropriate technical resources and infrastructure support.
  • Provide operational updates and reports to Research Computing leadership.

Team Leadership & Management

  • Supervise, mentor, and develop research computing team members.
  • Establish priorities, assign workloads, and oversee daily service delivery.
  • Support employee performance management, professional development, hiring, and onboarding.
  • Promote collaboration, accountability, and continuous improvement across the team.

Operational Reporting & Business Process Analysis

  • Develop annual, monthly, and ad hoc reports on computing resources, system utilization, storage services, and infrastructure capacity.
  • Analyze operational metrics to support purchasing decisions, resource allocation, and strategic planning.
  • Evaluate and improve research project workflows and service delivery processes.
  • Support research computing projects involving secure research environments and regulated data systems.
  • Collaborate on chargeback models, resource utilization, and service management processes.

Training & Documentation

  • Coordinate technical training programs for academic researchers, faculty, staff, and technical teams.
  • Manage synchronous and asynchronous training initiatives.
  • Coordinate the development of video tutorials, technical guides, and educational materials.
  • Maintain and update research computing documentation, knowledge bases, and technical resources.
  • Promote knowledge sharing and effective use of research computing services.

Required Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related technical field, or equivalent professional experience.
  • Demonstrated experience managing AI/ML infrastructure, research computing, high-performance computing, or related technical environments.
  • Strong understanding of AI/ML infrastructure requirements, GPU computing, accelerators, and high-performance computing resources.
  • Experience with containerized computing environments and AI/ML workflows.
  • Knowledge of MLOps tools, machine learning infrastructure, and model deployment environments.
  • Experience leading technical projects and coordinating cross-functional teams.
  • Previous experience supervising, mentoring, or managing technical professionals.
  • Strong understanding of IT infrastructure, compute resources, storage systems, and research technology environments.
  • Experience with operational reporting, resource utilization, and business process analysis.
  • Excellent communication and stakeholder management skills.
  • Ability to work with faculty, researchers, academic departments, and technical leadership.
  • Strong organizational, analytical, and problem-solving skills.

Preferred Qualifications

  • Experience working in a university, academic research, or scientific computing environment.
  • Experience managing High-Performance Computing (HPC) environments.
  • Hands-on knowledge of GPU clusters, NVIDIA GPUs, accelerators, and AI compute infrastructure.
  • Experience with Kubernetes, Docker, containers, and orchestration technologies.
  • Familiarity with MLOps platforms, machine learning pipelines, and AI model-serving infrastructure.
  • Experience supporting AI-intensive research projects and grant-funded research initiatives.
  • Knowledge of secure research environments, regulated research systems, and research data governance.
  • Experience developing technical roadmaps, infrastructure strategies, and capacity planning initiatives.
  • Experience managing research computing services and technical support teams.

Technical Skills & Search Keywords

AI Infrastructure | AI/ML Infrastructure | Artificial Intelligence | Machine Learning | Research Computing | High-Performance Computing (HPC) | GPU Computing | NVIDIA GPUs | GPU Clusters | Accelerated Computing | MLOps | Kubernetes | Docker | Containerization | Model Deployment | Model Serving | AI Workflows | Cloud Infrastructure | Data Pipelines | Research Data Infrastructure | Infrastructure Planning | Capacity Planning | Technical Roadmap | HPC Management | Research IT | IT Operations | Team Leadership | Project Management | Resource Utilization | Secure Research Environments

Ideal Candidate Job Titles

  • Manager, AI Infrastructure
  • AI Infrastructure Manager
  • Research Computing Manager
  • High-Performance Computing (HPC) Manager
  • HPC Infrastructure Manager
  • AI/ML Platform Manager
  • Machine Learning Infrastructure Manager
  • Research IT Manager
  • Director of Research Computing
  • AI Engineering Manager
  • Technical Infrastructure Manager
  • Research Computing Technical Lead
  • Scientific Computing Manager

Work Arrangement & Schedule

  • Hybrid work arrangement.
  • Must be local to Boston, MA.
  • 40 hours per week.
  • 9-month contract.
  • Collaboration with university researchers, faculty, and IT leadership.

Contract Details

  • Job Title: Manager, AI & Research Computing Initiatives
  • Job ID: 3743
  • Client: Boston University
  • Location: Boston, MA
  • Duration: 9 Months
  • Work Arrangement: Hybrid – Local Boston candidates only
  • Schedule: 40 Hours per Week

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