Staff Machine Learning Engineer - Generative AI Platform

Infoblox • Burnaby, BC

59d • Hybrid

About The Position

At Infoblox, every breakthrough begins with a bold “what if.”
What if your ideas could ignite global innovation?
What if your curiosity could redefine the future?

We invite you to step into the next exciting chapter of your career journey.
Bring your creativity, drive, your daring spirit, and feel what it’s like to
thrive on a team big enough to make an impact, yet small enough to make a
difference. Our cloud-first networking and security solutions already protect
70% of the Fortune 500, and we’re looking for creative thinkers ready to push
that influence even further. Join us and discover how far your bold “what if”
can take the world, your community, and your career.

How we empower our people is extraordinary: we’re recognized as a Glassdoor Best
Place to Work 2025, Great Place to Work-Certified in five countries, and honored
by Cigna as a Healthy Workforce honors for three consecutive years; and what we
build is world class: named CybersecAsia’s Best in Critical Infrastructure
2024 — clear evidence that when first-class technology meets empowered talent,
remarkable careers take shape. So, what if the next big idea, and the next great
career story, comes from you? Become the force that turns every “what if” into
“what’s next.”

In a world where you can be anything, Be Infoblox.

We are looking for a Staff Machine Learning Engineer – Generative AI Systems to
join our innovative AI team. In this pivotal role, you will design and deliver
enterprise-grade AI/ML systems, product copilots, and agentic AI solutions that
power the next generation of networking and security experiences. You will
collaborate closely with Product, Engineering, Security, and Platform teams to
bring scalable, secure, and high-impact AI systems into production.

Requirements

• 12 or more years of software engineering experience, including 4 or more years building and deploying Generative AI systems in production environments
• Strong experience designing and delivering scalable, production-grade machine learning or Generative AI systems from concept through deployment
• Deep understanding of large language models, prompt engineering, embeddings, and retrieval architectures (e.g., RAG)
• Hands-on experience building distributed backend systems and deploying services in cloud-native environments (e.g., AWS, GCP, or Azure)
• Experience with LLM orchestration frameworks, vector databases, and model APIs (e.g., OpenAI, Anthropic, Gemini, or open-weight models)
• Proven ability to establish evaluation, experimentation, and performance monitoring frameworks for AI systems
• Strong systems-thinking mindset with the ability to design reliable, secure, and scalable AI architectures
• Demonstrated technical leadership, including influencing cross-functional stakeholders and mentoring engineers in SaaS or large-scale distributed system environments
• Bachelor's/Master's degree or a PhD in Computer Science, Computer Engineering

Responsibilities

• Design and architect scalable Generative AI systems, including product copilots and internal AI tools, from concept through production deployment
• Build and productionize RAG pipelines, reasoning agents, embedding systems, and LLM orchestration frameworks integrated with enterprise tools and data platforms
• Establish evaluation, observability, and governance frameworks for Generative AI systems, including quality, safety, performance, and measurable business impact
• Implement enterprise-grade guardrails and security controls to mitigate hallucination, prompt injection, data leakage, and misuse
• Optimize AI system performance across cost, latency, reliability, and scalability in cloud-native environments
• Drive technical direction across cross-functional initiatives, partner with product and platform teams, and mentor engineers to elevate Generative AI best practices and architectural standards

Benefits

• Comprehensive health coverage, generous PTO, and flexible work options
• Learning opportunities, career-mobility programs, and leadership workshops
• Sixteen paid volunteer hours each year, global employee resource groups, and a “No Jerks” policy that keeps collaboration healthy
• Modern offices with EV charging, healthy snacks (and the occasional cupcake), plus hackathons, game nights, and culture celebrations
• Charitable Giving Program supported by Company Match
• We practice pay transparency and reward performance. Offers reflect role location, internal equity, experience, skills, education, and certifications.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level