Burnaby, BC, CanadaJob DescriptionAt Infoblox, every breakthrough begins with a bold“what if.”What ifyour ideas could ignite global innovation?What ifyour curiosity could redefine the future?We invite you to step into the next exciting chapter ofyourcareer 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 protect70% 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 aGlassdoor Best Place to Work 2025, Outstanding 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: namedCybersecAsia’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’snext.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.Be a Contributor — What You’ll DoDesign and architect scalable Generative AI systems, including product copilots and internal AI tools, from concept through production deploymentBuild and productionize RAG pipelines, reasoning agents, embedding systems, and LLM orchestration frameworks integrated with enterprise tools and data platformsEstablish evaluation, observability,



and governance frameworks for Generative AI systems, including quality, safety, performance, and measurable business impactImplement enterprise‑grade guardrails and security controls to mitigate hallucination, prompt injection, data leakage, and misuseOptimize AI system performance across cost, latency, reliability, and scalability in cloud‑native environmentsDrive technical direction across cross‑functional initiatives, partner with product and platform teams, and mentor engineers to elevate Generative AI best practices and architectural standardsBe Prepared — What You Bring12 or more years of software engineering experience, including 4 or more years building and deploying Generative AI systems in production environmentsStrong experience designing and delivering scalable, production‑grade machine learning or Generative AI systems from concept through deploymentDeep 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 systemsStrong systems‑thinking mindset with the ability to design reliable, secure, and scalable AI architecturesDemonstrated technical leadership, including influencing cross‑functional stakeholders and mentoring engineers in SaaS or large‑scale distributed system environmentsBachelor's/Master's degree or a PhD in Computer Science, Computer EngineeringBe Successful — Your PathFirst 90 Days:Immerse in our culture,



connect with mentors (Blox Buddies), and map the systems and meet with key stakeholders that rely on your work. Discuss and create short/long term goals.Six Months:Lead the end‑to‑end delivery of a production‑ready GenAI feature or systemEstablish measurable evaluation criteria for quality, safety, and business impactInfluence architectural standards for GenAI systems within the organizationOne Year:Drive significant improvements in engineering productivity, product intelligence, or customer experience through AI systemsEstablish reusable GenAI platform components adopted across multiple teamsBe recognized as a technical leader shaping our AI strategy and long‑term roadmapOur culture thrives on inclusion, rewarding the bold ideas, curiosity, and creativity that move us forward. In a community where every voice counts, continuous learning is the norm. So, whether you code, create, sell, or care for customers, you’ll grow and belong here.Comprehensive health coverage, generous PTO, and flexible work optionsLearning opportunities, career‑mobility programs, and leadership workshopsSixteen paid volunteer hours each year, global employee resource groups, and a “No Jerks” policy that keeps collaboration healthyModern offices with EV charging, healthy snacks (and the occasional cupcake), plus hackathons, game nights, and culture celebrationsCharitableGiving Program supported by Company MatchWe practice pay transparency and reward performance. Offers reflect role location, internal equity, experience, skills, education, and certifications. Base salary for this position: $135,000 - $204,300 plus bonusReady to Be the Difference?Infoblox is an Affirmintive Action and Equal Opportunity Employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, genetic information, age, disability, veteran status, or any other legally protected basis#LI-HP1#LI-HybridJob InfoJob Identification 7411Locations Infoblox Canada Ltd, BURNABY, AL, V5H 4M2, CAPosted Salary Range 135600.00 - 204380.00#J-18808-Ljbffr

📌 Staff Machine Learning Engineer - Generative Ai Platform - $135,000 - $204,300 A Year (Toronto)
🏢 Infoblox
📍 Toronto