Staff ML Infra Engineer, Search & Discovery

Job summary

We exist to wow our customers. We know we're doing the right thing when we hear our customers say, "How did I ever live without Cou***?" Born out of an obsession to make shopping, eating, and living easier than ever, we're collectively disrupting the multi-billion-dollar e-commerce industry from the ground up.

Benefits

Qualifications

• Join Cou*** now to create an epic experience in this always-on, high-tech, and hyper-connected world.
• If you are passionate about big data engineering and scalable serving systems, you want to make real business impact, and you are a true problem solver, this is the right job for you.
• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or
• closely related fields
• 5 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML
• systems
• Preferred
• Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning)
• Experience with Big Data

Responsibilities

• At Cou***, you will see yourself, your colleagues, your team, and the company grow every day.
• The Search & Discovery organization is responsible for optimizing customers' navigation experience and driving long-term growth.
• You will be handling billions of records of user interaction data, and petabytes of raw log files, and transforming them into data objects that can be easily consumed by engineers and scientists.
• You will also be responsible for serving complex ML models in real time to help millions of Cou*** customers search and discover products.
• Proactively drive the execution of end-to-end data platform, data quality roadmap for Search & Discovery ML efforts
• Take ownership, consolidate and optimize the Search & Discovery core data logging, processing, and ML model training pipelines
• Develop and scale data infrastructure that powers batch and real-time data processing, monitoring, and debugging for ML experiments
• Drive design and implementation of scalable ML based ranking system and online ML inference services
• Research, analyze and select technical approaches for solving difficult and challenging development and integration problems, coach and mentor other engineers in process and methodologies

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