Principal Data Scientist

At Albertsons Companies, we are looking for someone who’s not just seeking a job, but someone who wants to make an impact. In this role, you’ll have the opportunity to lead, innovate, and contribute to the growth of a company that values great service and lasting customer relationships. This position offers the chance to work in a fast-paced, dynamic environment that’s constantly evolving.

Building the future of food and well-being starts with you. Join our team and bring your best self to the table.

The position will be based in Pleasanton, CA.

• Lead the design and development of end-to-end deep learning solutions, from problem formulation and model architecture selection through deployment and continuous optimization within the Databricks Lakehouse platform.
• Serve as the technical authority for Graph Neural Networks (GNNs), graph representation learning, and advanced deep learning architectures, driving innovation and adoption across high-impact business problems.
• Architect scalable machine learning and deep learning platforms, establishing reusable frameworks, standards, and best practices for model development, deployment, and lifecycle management.
• Define and implement robust evaluation, explainability, and model governance frameworks to ensure model quality, transparency, and business impact.
• Lead the development and optimization of distributed training, large-scale data processing, and inference systems using Spark and modern AI infrastructure.
• Drive the fine-tuning, adaptation, and product ionization of foundation models, large language models (LLMs), and other advanced AI architectures leveraging enterprise data assets.
• Partner with Data Science, Engineering, Product, and Business leaders to translate strategic opportunities into scalable AI solutions that deliver measurable value.
• Influence AI strategy, technical roadmaps, and architectural decisions while mentoring senior practitioners and advancing organizational AI capabilities.

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Operations Research, or a related quantitative field strongly preferred.
• Master's degree with exceptional equivalent industry research and leadership experience may be considered.

• 12 plus years of experience developing and deploying machine learning and deep learning solutions in production environments.
• 8 plus years of experience leading advanced deep learning research, experimentation, and enterprise-scale implementation efforts.
• Demonstrated experience operating as a Principal Scientist, Principal AI Engineer, Distinguished Engineer, Research Lead, or equivalent senior technical individual contributor.

• Deep Learning
• Graph Neural Networks (GNNs)
• Graph Representation Learning
• Graph Embeddings
• Knowledge Graphs
• Graph Transformers
• Foundation Models and LLMs

• Apache Spark
• Py Spark
• Databricks Lakehouse
• Delta Lake
• MLflow
• Unity Catalog
• Expert knowledge of model training, optimization, serving, and lifecycle management across distributed GPU environments.
• Proven experience designing enterprise-grade inference systems balancing accuracy, latency, reliability, scalability, and operational cost.
• Advanced proficiency in Python and machine learning ecosystems including Num Py, Pandas, Scikit-learn, PyTorch, Tensor Flow, and related frameworks