Engineering at Postmates
We’re building groundbreaking tech solutions that power our revolutionary logistics platform to help connect millions of customers with their favorite merchants every day. We’re tackling some of the most complex technical challenges in the modern logistics space to unlock opportunities that positively impact the local businesses and communities we serve.WHAT WE DO
Postmates relies heavily on our engineering team to realize this vision. Building a software platform that is reliable, scales, and stays agile under demanding product needs is a serious technical challenge. Postmates is a three-part balancing act connecting customers, merchants, and couriers in real-time. If any piece is out of whack, the whole system suffers. Working with the Postmates engineering team offers an opportunity with explosive growth, cutting-edge technology, a highly visible charter, and a cool user-focused product vision.
In this role, you’ll have the opportunity to work on various challenging machine learning and optimization problems in real-time and in scale, including:
- Modeling and forecasting demand and supply to enable more intelligent matching, optimize the overall marketplace efficiency, and provide valuable insights to our merchants and Postmates
- Large scale Machine Learning algorithms and infrastructure that powers our Search Ranking models and Personalized Recommendation Engine
- Predicting the Postmates Delivery Time (PDT) and improving the efficiency (batching, chaining, etc) and reliability of the dispatching algorithm
- Determining the optimal pricing strategies to help our Postmates maximize their revenue
- Identifying suspicious transactions and malicious users for risk control
- Natural Language Processing to understand text content on Postmates platform, including named entity resolution and recognization of reviews, descriptions and interactions between users on our marketplace
- Build end-to-end ML systems of designing, training, testing and deploying Machine Learning models
- Write production-level codes to train your ML models into working pipelines and services to serve production online traffic
- Have the ability to apply machine learning to solve complex business problems and optimize critical business metrics, and work closely with Product Managers and Data analysts to frame Machine Learning problems within the business context
- Analyze experimental and observational data, communicate findings, and facilitate launch decisions
- Participate in code reviews to ensure code quality and distribute knowledge
- A Bachelor’s/Master’s degree (or higher) in a technical field (Computer Science, Statistics, Economics, Operations Research, Math, Physics, Engineering, etc.) or equivalent work experience required.
- Minimum of 3+ years of professional experience in Data Science or Applied Machine Learning required
- Solid engineering and coding skills with the ability to write high-performance production quality code
- Good understanding of common families of machine learning models, feature engineering, feature selection and other practical machine learning issues, such as overfitting
- Strong communication skills. Explaining complex technical concepts to product managers, data analysts, and other engineers shouldn’t be a problem for you.
- Industry experience building and productionizing innovative end-to-end Machine Learning systems
- Experience in Java, C++, Go, Python, Scala and other equivalent languages
- Experience with MapReduce, Spark, Hive, HBase, Airflow, Google BigQuery, BigTable, and Dataflow
- Experience with ML frameworks like Tensorflow, PyTorch, Spark MLlib, XGBoost, and Scikit-Learn