What are the responsibilities and job description for the Senior Infrastructure Engineer position at Acceler8 Talent?
Senior SW / Infrastructure Engineer
We’re hiring a SW / Infrastructure Engineer to join a well-funded MIT spin-out based in Cambridge that’s building the infrastructure backbone for efficient, enterprise-grade AI.
The team is developing an AI optimization platform that helps large enterprises train, deploy, and operate machine learning models 2–15× faster and up to 90% cheaper. The platform spans training, fine-tuning, inference, and deployment — enabling teams to ship production AI in minutes rather than months.
They are already working with multiple Fortune 500 organizations, have several live enterprise PoCs underway, and are backed by top-tier investors, including a major cloud provider’s venture arm, a leading early-stage fund, and a top US technical accelerator. Clear market comparables include recent billion-dollar outcomes in the AI infrastructure space.
What you’ll do:
- Design and build the infrastructure that powers large-scale ML training, deployment, and monitoring
- Operate Kubernetes at depth (Helm, CRDs, Operators, controllers, RBAC) tailored for ML pipelines
- Build Go-based tooling for model distribution, versioning, rollbacks, and secure artifact delivery
- Own Terraform GitOps workflows to enable reproducible, governed enterprise deployments
- Work closely with founders, ML researchers, and early enterprise customers
- Make foundational architecture decisions in a fast-moving, early-stage environment
What we’re looking for:
- Senior or Principal-level experience in software, infrastructure, or platform engineering
- Strong Kubernetes experience beyond basic usage (operators, custom controllers, platform abstractions)
- Production Go experience building internal tooling or distributed systems
- Experience with Terraform, GitOps, and cloud-native infrastructure
- Comfortable operating in high-ownership, founder-led startup environments
Bonus: experience supporting ML training, inference, or data-intensive workloads
Location: Onsite, Cambridge, MA (5 days/week preferred)
Visa: Sponsorship possible if already based in the US
Compensation: Competitive salary meaningful early-stage equity