Forward Deployed Engineer - AI Inference Systems Research

About the Team:

Your Role:

• Customer Deployments & Issue Triage
• Partner directly with enterprise customers to deploy, configure, and validate Nutanix Enterprise AI workloads across hybrid multi-cloud and on-premises environments.
• Perform root-cause analysis on real-time failures spanning GPU orchestration, container networking, storage I/O bottlenecks, and model runtime crashes.
• Serve as the frontline technical authority, driving critical customer incidents to resolution through hands-on debugging across Linux internals, hypervisors, and Kubernetes clusters.
• Solutions Engineering & Tooling
• Identify recurring patterns in customer configurations, support tickets, and performance regressions.
• Develop production-grade automation scripts, CLI tools, Helm charts, and reference architectures to streamline deployment pipelines across heterogeneous environments.
• Feed operational insights, reproducible test beds, and code patches back to the core NAI product engineering teams.
• Inference Systems Research & Optimization
• Experiment with, evaluate, and benchmark modern inference frameworks (e.g., vLLM, TensorRT-LLM, TGI, Triton Inference Server).
• Profile model inference pipelines to optimize latency, throughput, time-to-first-token (TTFT), and inter-token latency (ITL) on modern accelerator architectures (NVIDIA, AMD).
• Prototype applied techniques such as speculative decoding, KV cache management strategies, continuous batching, and quantization (AWQ, FP8, GPTQ) for platform integration.
• What You Will Bring
• Education: Ph.D./Master’s degree in Computer Science, Computer Engineering, Artificial Intelligence, or a related quantitative field with 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.
• Learn More About the Technology: https://www.nutanixbible.com/
• #NAI
• Highlighted Benefits (Vancouver, Canada)
• Retirement: RRSP with dollar-for-dollar matching up to 7% of base salary
• Mental Health: Dedicated mental health coverage plus top-tier paramedical benefits
• Family: Fully paid maternity and parental leave and generous bereavement leave, including time for the loss of a pet
• Equity: RSUs and Employee Stock Purchase Plan at a 15% discount
• Time Off: Company holidays, sick days, company wellness days, and vacation starting at 10 days
• Work Arrangement Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. In locations where our workplace policy applies (i.e. San Jose, Durham, Mexico City, Vancouver, Bangalore, Pune, Hoofddorp, Belgrade, Barcelona, Singapore, Sydney and Tokyo), employees are expected to work onsite a minimum of 3 days per week to foster collaboration, team alignment, and access to in-office resources. Workplace type may vary based on location and team requirements. Please speak with your recruiter for details. Additional team-specific guidance and norms will be provided by your manager.
• 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.

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.
• Learn More About the Technology: https://www.nutanixbible.com/
• #NAI
• Highlighted Benefits (Vancouver, Canada)
• Retirement: RRSP with dollar-for-dollar matching up to 7% of base salary
• Mental Health: Dedicated mental health coverage plus top-tier paramedical benefits
• Family: Fully paid maternity and parental leave and generous bereavement leave, including time for the loss of a pet
• Equity: RSUs and Employee Stock Purchase Plan at a 15% discount
• Time Off: Company holidays, sick days, company wellness days, and vacation starting at 10 days
• Work Arrangement Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. In locations where our workplace policy applies (i.e. San Jose, Durham, Mexico City, Vancouver, Bangalore, Pune, Hoofddorp, Belgrade, Barcelona, Singapore, Sydney and Tokyo), employees are expected to work onsite a minimum of 3 days per week to foster collaboration, team alignment, and access to in-office resources. Workplace type may vary based on location and team requirements. Please speak with your recruiter for details. Additional team-specific guidance and norms will be provided by your manager.
• 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.