H-E-B's Corporate Planning and Analysis Team is looking to develop and maintain budgets and financial systems while providing current, reliable financial data, analysis, and technical information to drive business decision-making.
Requirements
- Technical knowledge in programming languages: SQL, R, Python, Scala, Java, C/C++
- Technical knowledge in big data / ML optimization: GPU code optimization, Horovod, Spark MLlib optimization, Cython, JNI, Numba
- Technical knowledge in mainstream ML / AI: manifold learning, distributed clustering, graph network, hierarchical model, Bayesian network, deep learning, computer vision, NLP/NLU, reinforcement learning, meta-Learning, federated learning
- Expertise in ML visualization flow
- Expertise in optimizing distributed machine learning in a heterogeneous domain environment
- Technical skills to consider and apply causal reasoning representation and learning, and human-centric, explainable, responsible AI
- Ability as a creative storyteller and translator between business questions and ML solutions
Responsibilities
- Handles the design, creation, and maintenance of an ML platform and related environments.
- Manages Docker containers and Kubernetes clusters, oversees dependencies and configurations, and implements CI/CD pipelines for automated building, testing, and deployment of machine learning models.
- Monitors and optimizes model training performance and resource usage.
- Deploys ML models to production environments and manages model versioning and rollback mechanisms.
- Ensures scalable and reliable model serving using tools like Vertex, Databricks, TensorFlow Serving, Flask, or FastAPI, ensuring the infrastructure can scale to meet the growing demands as the complexity and number of ML models increase.
- Architects and develops Generative AI solutions utilizing Machine Learning and GenAI techniques.
- Handles both unstructured and structured data, preparing it to be used as context for Language Model Learning (LLM).
Other
- A related degree or comparable formal training, certification, or work experience
- 7+ years of experience in a retail or retail-related decision science role
- Ability to work in a fast-paced retail environment with frequently shifting priorities
- Ability to work extended hours; sit for long periods
- Willingness to mentor
