Staff Machine Learning Engineer

Job Overview Staff Machine Learning Engineer - GenAI at Kraft Heinz. You will lead engineering for agentic, domain-focused “expert” services on Kraft Heinz AI (KHAI). You will convert research notebooks and PoCs into production‑grade, low‑latency microservices, orchestrate LLMs with tools, retrieval, and enterprise data, and collaborate with the GenAI CoE, product, security, and platform teams. Key Responsibilities Design & build GenAI microservices (REST/SDKs) with clear SLOs, strong observability, and multi‑tenant controls; ensure seamless integration with KHAI and enterprise systems. Build agentic AI workflows on Copilot Studio; integrate KHAI agent services into enterprise workflows and enable scalable automation. Productionise models & agents, hardening PoCs into resilient components (retry, idempotency, versioning, circuit breakers, fallbacks, canary/blue‑green) with CI/CD for code and models. Engineer agentic workflows tool use, retrieval (RAG), memory, planning, and policy/guard layers to deliver task‑level outcomes rather than single‑step responses. Optimize for latency, throughput, and cost profile/model batching, async I/O, caching, vector I/O, and right‑sizing CPU/GPU to meet experience and unit‑economics targets. Build ML pipelines to automate data prep, training, evaluation, packaging and deployment; integrate with feature stores, model registries and inference gateways. Integrate with Microsoft ecosystem; collaborate with Copilot Studio/Power Platform teams to connect KHAI agent services with conversational bots and workflow automations. Establish quality & testing: golden datasets, prompt/model evaluation harnesses, unit/contract/integration/performance tests, and regression gates (quality, drift, bias). Qualifications 8+ years in software engineering, including 4+ years building and operating ML/AI applications or microservices in production. Strong Python and software fundamentals (design patterns, testing, performance profiling). Experience shipping RESTful/gRPC services at scale. Proven record taking models from prototype to production (feature stores, model registries, packaging, inference patterns/batching). Solid grasp of the ML lifecycle: data prep, training, evaluation, deployment and monitoring (quality, drift, bias) with incident response. Cloud fluent (Azure preferred; AWS/GCP welcome) across compute, storage, networking, and AI/ML services. Experience in containers & orchestration (Docker, Kubernetes), and CI/CD for both code and models. Excellent communication and stakeholder skills; able to influence across DS, product, platform, security, and business teams. Compensation New Hire Base Salary Range: $120,100.00 – $150,100.00 Bonus: Performance‑based bonus as provided by the plan terms and governing documents. The compensation offered will take into account internal equity and may vary depending on the candidate's geographic region, job‑related knowledge, skills, and experience among other factors. Benefits Physical: Medical, Prescription Drug, Dental, Vision, Screenings/Assessments Social: Paid Time Off, Company Holidays, Leave of Absence, Flexible Work Arrangements, Recognition, Training Emotional: Employee Family Assistance Program, Wellbeing Programs, Family Support Programs Financial: Savings/Pension, Life, Accidental Death & Dismemberment, Disability, Discounted Perks Location Toronto – Queen's Quay – Headquarters Equal Opportunity Statement Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes. In order to ensure reasonable accommodation for protected individuals, applicants that require accommodation in the job application process may contact NAZTAOps@kraftheinz.com for assistance. #J-18808-Ljbffr