Senior Research Engineer

Yext makes software and tools to improve everyone’s experience on the internet by providing perfect answers everywhere. Our clients trust us to use natural language processing (NLP) and machine learning (ML) to deliver correct information to end users and to help every company solve their Answers Problem.

As a Senior Research Engineer you will build tools and systems that solve challenging problems in natural language processing, information retrieval, and machine learning. Your tools and systems will enable and empower researchers and data scientists, and help shape algorithms to develop essential new capabilities and features for Yext’s products. We manage large amounts of structured master data on behalf of some of the world’s largest companies and collect transactional data through end-user-facing applications we host directly for these clients. 

Yext clients cover a tremendous breadth of industries. We are seeking a research engineer  excited to discover opportunities in data across a wide variety of business domains. You will work collaboratively with cross-team partners in software engineering, product management, and strategy. This approach will allow you to participate fully in the product development lifecycle and make pragmatic decisions about the design, training, and deployment of machine learning models driving key product features. 
What You'll Do

• Write high quality Python code (we use PyTorch, TensorFlow and Transformers in many places) to support and sustain ambitious and audacious research problems 
• Build, maintain and enhance data pipelines and automated training jobs 
• Mentor junior team members, provide technical leadership and execution guidance  
• Exercise excellent technical judgment and prioritization around complexity, completeness, details and risks
• Communicate data science and machine learning concepts to other engineers less experienced in the art
• Partner with product management and engineering teams throughout the product development lifecycle 

• Ability to write elegant, idiomatic and modern Python
• Experience with best and state-of-the-art practices in CI and CD for machine learning (including containerization and MLOps) 
• Experience with state of the art methods in machine learning (both supervised and unsupervised), deep neural networks, and information retrieval (e.g. HNSWs)
• Autodidactic, self directed – you are able to dive into a new unfamiliar problem domain and learn quickly in the face of adversity – you are comfortable with uncertainty and project evolution
• Excellent ability to solve "glue" problems (e.g. shell scripting, python environment setup, efficient programming practices), and to assist, improve and generalize solutions to such problems for other scientists on the team
• Highly developed communication skills (verbal, written and graphical) 
• Experience leading cross-functional agile work streams and scaling data-driven initiatives  
• Multi-tasking, project management, and leadership skills. 

• Experience in TensorFlow or PyTorch, and state-of-the-art transformer/NLP models and techniques (e.g. FastText, BERT, et al.).
• NLP experience, especially with sentence embeddings. 
• Very experienced in data warehousing and specific tools such as Snowflake, MySQL and other cloud or distributed databases 
• Experience with common quantitative analysis and ML packages (in Python or R) such as Pandas, Matplotlib, ggplot, scikit-learn and scipy. 
• Experience with JVM languages (Java, Scala) a plus. GoLang or C++ also great! 
• Experience with AWS, Linux and Mac environments
• Knowledge of statistics and good experimental practices (e.g. how to run a powerful A/B test and test for significance)
• Knowledge of techniques in unsupervised machine learning and information retrieval and mining (e.g. DBSCAN, k-Means, indexes)

#LI-JB2

The base salary at the time of hire for this position is expected to be between $149,850 - $249,500. Pay ranges at Yext are established based on an analysis of salaries for positions with a similar level of accountability and impact in the relevant labor market. Salary levels are expected to change to reflect an employee’s job performance (results and impact) over time. Salaries at the time of hire are typically offered in the lower to middle of the above-referenced range in order to provide the opportunity to reflect performance-based increases over time. In addition to base salaries, employees at Yext are typically eligible for a comprehensive package of benefits, and successful candidates may also be eligible for equity (stock) based compensation and/or variable pay programs based on performance relative to goals and targets.