Tech Lead

About this role

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Senior Machine Learning Engineer

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Machine Learning Engineer

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Skills you'll use

What you'll do

• ML Engineering Leadership
• Lead and mentor ML Engineers and Data Scientists across multiple AI/ML initiatives.
• Define engineering standards, reusable frameworks, reference architectures and code-quality practices for ML solutions.
• Own technical design and code reviews, production-readiness reviews and complex problem resolution.
• Drive scalability, reliability, maintainability, security, performance and cost efficiency across AI products.
• Machine Learning Architecture
• Design end-to-end ML architectures covering data, feature engineering, training, evaluation, registry, deployment, monitoring and retraining.
• Define batch and real-time inference patterns, model serving strategies, feature management, model versioning and rollback mechanisms.
• Establish reproducible experimentation, validation and model lifecycle standards.
• Generative AI & LLM Engineering

Who can apply

• Strong programming skills in Python and SQL; experience with PyTorch, TensorFlow and/or scikit-learn.
• Strong knowledge of FastAPI/REST APIs, microservices, Docker and Kubernetes.
• Hands-on expertise in Machine Learning, Deep Learning, NLP, Generative AI, LLMs, RAG, embeddings, vector databases and prompt engineering.
• Practical knowledge of Agentic AI, LLM evaluation, AI guardrails and responsible AI.
• Good understanding of Spark, data pipelines, distributed processing, Delta Lake/data-lake patterns, feature engineering and data quality.
• Experience with MLflow, Azure ML, Databricks, Kubeflow and/or comparable MLOps platforms.
• Experience with GitHub Actions, Azure DevOps or equivalent CI/CD tooling.

About AB InBev

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