Abercrombie & Fitch Co. is a portfolio of lifestyle brands including Abercrombie & Fitch, abercrombie kids, Hollister, and Gilly Hicks. Reaching customers across 120+ countries, we strive to create customer-centric, omni-channel experiences for our global customer base.
How do we do it? Every day, our associates show up and empower one another to stay curious and think big. As a team of relentless innovators, we aren’t afraid to dream boldly. We are accountable and aim to the highest caliber to understand, push boundaries and embrace change. We coach, mentor, care, and bring our best selves every day because we are in this together. Whether you lead yourself, a team, or the company, everyone is a leader at A&F.
The A&F Corporate Data & Analytics team is committed to scaling predictive analytics across the organization. In order to scale, we need an ambitious and gritty Machine Learning Data Engineer to champion of accuracy, reproducibility, and resiliency. This person will be critical to shortening development cycles for new insight products by reducing technical debt. The ML Data Engineer will leverage comprehensive working knowledge of MLOps as well as Data Engineering best practices to enable data scientist team members to become full-stack – owning projects end-to-end, from data exploration to model deployment.
What will you be doing?
- Data Engineering
- Collaborate with Data Engineering team in Design Reviews and performance improvements of new and existing machine learning data pipelines.
- Design and build robust data integrations between cloud data platform and 3rd party data sources to enable low-code data ingestion.
- Machine Learning Pipeline Management
- Design and deploy a machine learning pipeline from exploratory query to feature engineering to model training/testing to production batch or real-time deployment.
- Develop best practices and how-to guides for MLOps practices such as:
- Input data unit and statistical testing
- Experiment tracking
- Model registry
- Scheduling of ML pipelines
- Production drift monitoring and alerting
- Optimization of cloud compute resources
- Serve as the MLOps SME (Subject Matter Expert) and coach for the entire Data & Analytics team
- Train all data scientists in MLOps best practices to enhance reproducibility and resilience of custom A&F insight products.
What will you need to bring?
- B.S. degree or above in Software Engineering, Computer Science Engineering, Machine Learning Engineering or related engineering fields
- You don’t have to be an expert in all or any of the areas below, but we need someone with a passion for learning and growing as a software developer and ML Data engineer.
- Strong engineering and coding skills, with ability to write high quality production code.
- Expert in Python, SQL, PySpark, JSON, and/or CLI.
- Experience with Azure cloud ecosystem
- 3+ years of production ELT experience
- 2+ years of production model deployment experience
- Experience optimizing model hyperparameter tuning for speed and cost
- Experience building supervised and unsupervised models
- Experience developing with Agile practices.
- Excellent documentation habits
- Highly motivated/self-starter with a sense of ownership, willingness to learn, and desire to succeed.
- You don’t have to be an expert in all or any of the above areas but we need someone with a passion for learning and growing as a software developer and ML engineer