Senior Machine Learning Engineer, Instacart

• Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience
• Have 3+ years of industry experience using machine learning to solve real-world problems with large datasets
• Have strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and Machine Learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
• Have strong analytical skills and problem-solving ability
• Are a strong communicator who can collaborate with diverse stakeholders across all levels

Desirable

• As a Senior Machine Learning Engineer, you will utilize your extensive technical knowledge to address and solve critical, complex issues in our marketplace systems
• You will apply machine learning/AI to create and optimize solutions in impactful areas such as routing optimization, pricing, dispatch and mapping
• You will be at the forefront of initiatives, overseeing them from the initial concept stage all the way through to prototyping and implementation, in addition to conducting experiments
• The Logistics AI group is responsible for the intelligence and execution behind Instacart’s fulfillment system
• The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high quality, shoppers get efficient and fulfilling work, and retailers and consumer brands get reasonable business
• The team tackles hard problems in a variety of spaces, such as matching, pricing, and geospatial, as well as foundational problems executing on a high throughput system with dynamic data
• Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace
• Collaborate closely with product managers, data scientists, and backend engineers to deeply understand business needs and create impactful ML applications
• Actively engage with diverse stakeholders to ensure that solutions are well-integrated and aligned with business goals
• Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models