Interested in working with one of the largest fashion and e-commerce datasets in the worlds? Tired of prototyping machine learning models that don’t make it into production? This is great time to be joining Macy’s as a machine learning engineer and be embedded in one of our lean labs that are responsible for personalizing the customer journey on Macy’s.com.
You will help contribute to our large-scale, real-time machine learning ecosystem that enables our customers to find the most inspiring and relevant products on our website. For that we employ a range of machine learning techniques, such as:
- Real-time personalization recommendations
- Personalized search ranking
- Customer segmentation
- Deep learning computer vision models
- Deep learning recommendation models
- Contextual multi-arm bandits
We use these techniques to optimize the content on our home page, return the most relevant search results and surprise our customers with interesting fashion products.
You will be working in a lean lab setting. This means you will collaborate directly with data engineers, software engineers and product managers to bring your algorithms to life. These lab are empowered to move independently, so they can test models at a fast pace.
We are looking for machine learning engineers that have a strong mathematical background and are capable of working with software engineers to implement new algorithms on our machine learning platforms. We are expecting candidates to have previously prototyped and scaled machine learning models in a related field. Great communications skills are important for sharing your insights and influence the teams. Furthermore, you should be comfortable working independently and have a strong focus on productionalizing new models.
We work on relevance algorithms from information retrieval, machine learning and ranking to deliver a high-availability, low-latency service, which directly impacts business metrics. Your duties include:
- Responsible for proposing new models or improving our existing models in line with our business goals
- Responsible for building machine-learning pipelines optimized for our production infrastructure
- Responsible for the continuous evaluation of the quality of our machine-learning ecosystem
- Discover trends and patterns in datasets to identify new opportunities
- Support software engineers developing and evaluating machine-learning pipelines
- Support analysts and product managers with advanced statistical analysis on log or reporting datasets
- Contribute to sharing and developing best-practices
- Contribute to our machine-learning development lifecycle process
- Contribute to support systems including monitoring, reporting and serving solutions
- Responsible for researching new trends in the industry and utilizing up-to-date technology
- Work with cross-functional partners across the business.
- PhD in computer science, mathmatics or similar field or MS with at least 2-5 years of related experience
- Deep knowledge of machine learning, information retrieval, data mining, statistics, or related field.
- Strong analytical skills
- Strong functional coding skills in Python, Scala, Java or C++,.
- Strong preference for hands-on experience with TensorFlow, Scikit-learn, PredictionIO, Spark MLlib, H2O or other ML Libraries
- Experience working with large data sets and distributed computing tools a plus (Map/Reduce, Hadoop, Hive, Spark etc.)
- Apparel & Fashion
- Information Technology & Services
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1