Why choose us?
Are you ready to take the next step in your career? Join us for an exciting opportunity at Albertsons Companies, where innovation and customer service go hand-in-hand!
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.
Bring your flavor
Building the future of food and well-being starts with you. Join our team and bring your best self to the table.
Main responsibilities:
- Design end-to-end deep learning model development, from problem framing and target definition through architecture selection, training strategy, evaluation, and iteration within a Databricks Lakehouse environment
- Architect and build end-to-end deep learning pipelines, from data ingestion and feature engineering to training, deployment, scaling, and monitoring
- Build rigorous evaluation frameworks using offline metrics and explainability methods such as SHAP-based feature importance and prediction-level explanations.
- Implement distributed training and large-scale data processing using Apache Spark
- Build scalable batch and real-time inference pipelines integrated with Databricks workflows
- Lead fine-tuning and adaptation of large models and foundation models using custom data, with checkpoints, experiments, and model artifacts tracked in MLflow and prepared for governed deployment
- Optimize data pipelines and model performance for scalability, latency, and cost efficiency
Collaborate with cross-functional teams to productionize ML solutions on the Lakehouse
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The position will be based in Pleasanton, CA.
We are looking for candidates who possess the following:
Required Qualifications
- Proven experience leading deep learning model development for complex business problems, including problem formulation, experimentation, evaluation, and productionization.
- Strong hands-on expertise in PyTorch or TensorFlow and modern neural architectures, with experience scaling training using multi-GPU or distributed approaches
- Deep hands-on experience with Databricks, including Delta Lake, Spark, and MLflow, Unity Catalog, governance, and security
- Strong experience with distributed computing and large-scale data processing (Apache Spark)
- Proficiency in Python and ML/data ecosystems (NumPy, Pandas, Scikit-learn, PySpark)
- Strong understanding of feature engineering and data pipeline design in a Lakehouse architecture
- Expertise in distributed training and inference (multi-GPU, multi-node systems)
- Experience designing high-throughput, low-latency inference systems
Experience building feature stores and reusable ML components within Databricks
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Preferred Qualifications
- Experience deploying large-scale deep learning models (e.g., LLMs, recommendation systems) on Databricks
- Experience with cloud platforms (AWS, Azure, GCP) alongside Databricks
- Experience with streaming pipelines (Structured Streaming, Kafka integration)
- Experience with generative AI, LLM fine-tuning, or foundation models
Background in retail, e-commerce, or supply chain analytics
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We also provide a variety of benefits including:
- Competitive wages paid weekly
- Access to up to 50% of your earned wages before payday, via our partnership with Stream
- Associate discounts
- Health and financial well-being benefits for eligible associates (Medical, Dental, 401k and more!)
- Time off (vacation, holidays, sick pay). For eligibility requirements please visit myACI Benefits
- Leaders invested in your training, career growth and development
- An inclusive work environment with talented colleagues who reflect the communities we serve
Our Values – Click below to view video: ACI Values
A copy of the full job description can be made available to you.
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