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Nutanix, a company built on selling hyperconverged infrastructure to IT departments, is putting engineers inside customer sites to get enterprise GPT and LLM deployments running, which signals a push to own the AI inference layer on-premises rather than leave it to cloud providers.
Hungry, Humble, Honest, with Heart.
The Opportunity
When people talk about generative AI and other ML-powered solutions in today's conversation, they often refer to generative pre-trained transformers like ChatGPT that can respond to queries from a position of deep learning. A GPT-in-a-box solution removes the burden of building or implementing these AI solutions yourself. It also makes overcoming the complexity, inefficiency, and security challenges of generative AI and AI/ML applications easy. Nutanix simplifies your learning curve on AI-ready infrastructure with Nutanix Cloud Platform for AI (GPT-in-a-Box). This high-performant Machine Learning full-stack cloud platform helps you optimise IT costs with a software-defined cloud operating model. Harness AI-ready capabilities right out of the box, simplified to build, fine-tune, and run models, including GPTs and LLMs, while you continue to use existing teams and skills.
Join the Nutanix AI team, responsible for the magic behind the scenes.
About the Team:
The Nutanix AI Solutions Engineering and Forward Deployed Engineering (FDE) team operates at the critical intersection of applied research, systems engineering, and customer success. Our charter spans three core pillars:
Role Overview
As an entry-level Forward Deployed Engineer based out of our Vancouver office, you will bridge the gap between Nutanix AI product engineering, cutting-edge systems research, and enterprise production environments. You will deploy end-to-end AI infrastructure on the Nutanix Cloud Platform, diagnose complex distributed systems failures, and design programmatic solutions that prevent recurring deployment friction. Additionally, you will dedicate structured time to inference research—evaluating emerging open-source inference engines, optimizing GPU utilization, and benchmarking model serving performance.
You will report to a seasoned Technical Manager who will provide mentorship and guidance as you navigate through your responsibilities. The work setup at Nutanix AI is a hybrid model, offering a blend of in-office collaboration and remote work flexibility. As a new hire, you will be expected to be in the office for 3 days a week, ensuring that you have the opportunity to engage with your team and foster strong working relationships.
Your Role:
What You Will Bring
Education: Ph.D. in Computer Science, Computer Engineering, Artificial Intelligence, or a related quantitative field with an academic or thesis focus on AI/ML systems, distributed systems, operating systems, or computer architecture.
Programming: Strong proficiency in Python and C++ or Go, with an emphasis on systems programming, concurrency, and API development.
Systems & Infrastructure: Deep theoretical and practical knowledge of Linux operating systems, systems performance profiling, containerization (Docker), and container orchestration (Kubernetes).
AI/ML Runtimes: Hands-on experience deploying, serving, or profiling Large Language Models (LLMs) and diffusion models using PyTorch and open-source serving frameworks (vLLM, Hugging Face TGI, Triton).
Communication: Ability to distill complex distributed systems failures into clear technical action plans for both customer stakeholders and internal engineering teams.
Preferred Qualifications
Prior internship, research fellowship, or co-op experience in forward deployed engineering, site reliability, infrastructure engineering, or ML platform development.
Direct experience with hardware-aware optimization tools, such as CUDA, NVIDIA Nsight Systems, Triton kernels, or ROCm.
Familiarity with enterprise storage concepts (POSIX, S3/Object Store, NVMe-oF) and virtualization technologies (KVM, AHV).
Contributions to open-source inference runtimes, distributed ML libraries, or Kubernetes operators.
Note: Nutanix does not assist with applications for work permits or permanent residence, including provincial nomination.
Pay Transparency - Role Location The pay range for this position at commencement of employment is expected to be between CAD $132,000 and CAD $198,000 per annual.
However, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements, including a sign-on bonus, restricted stock units, and discretionary awards in addition to a full range of medical, financial and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors. Our application deadline is 40 days from the date of posting. In good faith, the posting may be removed prior to this date if the position is filled or extended in good faith.
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