Brazil
Pentera
iFood
Senior Staff AI/ ML Engineer
Brazil
Osasco, São Paulo, Brazil
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About the opportunity
Our way of doing things on the team
iFood moves over 80 million orders per month, and behind every incredible experience, we have Machine Learning models and AI agents making real-time decisions.
We are looking for the person who will define how AI operates at scale at iFood: someone who thinks beyond the model, sees the complete system, and translates strategy into a technical roadmap for the next 12-24 months. If you want to work at the intersection of high-performance engineering and the frontier of generative AI, leading multiple teams, mentoring engineers, and creating solutions that impact millions of users every day: this is your opportunity.
We are looking for someone passionate about innovation and technology, who is always seeking new learning opportunities and enjoys challenges. If you identify with this profile, we would love to meet you!
What are you hungry for?
We, FoodLovers, are hungry for innovation and results. We always strive to do our best, thinking "outside the box" and acting with agility and responsibility! We are hungry for diversity, knowledge, and sharing. We work in a very versatile environment. Do you know what makes our special recipe? People! Come be a part of it🤝
Your Daily Menu
- MLOps & Serving Strategy: Define the MLOps strategy for the organization. Design serving platforms that support multiple frameworks and paradigms (batch, real-time, agents). Establish CI/CD for ML models as an organizational standard, with formal governance (model cards, approval workflows, model registry).
- AI Agent Engineering: Define the AI agent strategy for the organization. Design architectures that scale to multiple domains, involving orchestration, tool calling, memory, RAG, evals, and guardrails. Design how agents interact with iFood's data semantic layer.
- FinOps & ML Infrastructure: Lead FinOps initiatives for ML: cross-team computational cost reduction, infrastructure migrations (on-demand to spot, GPU generations), intelligent auto-scaling. Design a platform that serves multiple teams with different needs.
- Responsible AI & Governance: Contribute to defining policies for responsible AI use (bias, fairness, safety, PII protection). Ensure model governance incorporates responsible AI. Implement robust guardrails against hallucinations, prompt injection, and data leakage.
- Mentorship & Technical Leadership: Mentor engineers and data scientists in MLOps and GenAI. Write RFCs and ADRs that define technical standards for the domain. Organize and strengthen the technical community (guilds, tech talks, shared standards). Elevate the technical bar across multiple teams.
- Health & Observability: Lead technical excellence of systems, creating plans for quality assurance and failure mitigation. Monitor regressions (drift, error rates) and coordinate system evolutions to maintain ML platform cohesion.
Minimum requirements
Ingredients We're Looking For
- MLOps Strategy at Scale: Experience defining MLOps strategy for multiple teams — not just operating, but designing how the organization takes models to production safely and reproducibly.
- AI Agent Architecture: Experience designing production agents that reason, use tools, and handle errors — including standardization of guardrails, evals, and organizational-level observability.
- FinOps for ML: Management of computational cost as a discipline — GPU, spot instances, auto-scaling — with a cross-team optimization view, not a point-in-time one.
- Model Governance: Model cards, registries, approval workflows, and auditability as a practice, not a checklist.
- Responsible AI: Experience defining or applying fairness, bias, and safety policies in models and agents.
- Technical Mentorship: Track record of multiplication — mentoring engineers, leading guilds, elevating technical standards in teams other than your own.
To Enhance the Flavor
- AI-operable Vision: Ability to think beyond the model, anticipating how the complete system will evolve — and translating that into a 12-24-month roadmap.
- Multi-tenant Platform: Experience designing ML platforms that serve multiple teams with different needs.
- Inner Source / Open Source: Contributions to projects beyond your domain — RFCs, ADRs, shared libraries.
- Leadership Advisory: Experience as a technical advisor to senior stakeholders, connecting AI strategy to business strategy.
- Applied Research: PoCs and research that introduced new capabilities to the team.
- Intermediate/Advanced English: For contact with international teams in the iFood ecosystem.
About Us
At iFood, we believe in the power of diversity to generate #Inovação and achieve incredible #Resultados, which is why we do not discriminate based on disability, gender, sexual orientation, race/ethnicity, age, origin, family structure, and appearance. We have groups composed of volunteer foodlovers, where we discuss Race, Gender, LGBTQI+, and People with Disabilities. We want to be the company where people choose to develop and contribute to making dreams come true, #AllTogether.
Discover our initiatives →
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