Senior Software Engineer II, Machine Learning

Narvar

8d•Remote

About The Position

Narvar is growing! We are hiring a Senior Software Engineer II to build new products and improve all aspects of the Narvar platform. Data is at the core of our competitive advantage so the work you do has a large impact across the company, our business partners, and the lives of our end users. Machine Learning Engineers at Narvar work across the stack. We are ‘full-stack’ ML Engineers. This means that we write production-level code and own machine learning operations for our teams.

Requirements

Strong machine learning skills.
Fluency in Python, PyTorch, Tensorflow, Pandas, numpy, and machine learning packages
Data Engineering skills and large data experience. You should have dealt with large amounts of data (TB) in a production setting, built world class data pipelines using cutting edge tools (e.g. Spark).
10+ years of hands-on experience shipping models to production, working on a variety of problem spaces (eg: user modeling, spam classification, prediction, clustering etc)
MS in Computer Science, Statistics, Math, Science (physical or social), Engineering or similar quantitative and computation field plus 5+ years of industry experience
Strong software engineering and coding skills with the ability to write production quality code
Strong understanding of probability & statistics, machine learning, and algorithms
Experience with SQL and NoSQL databases
Experience working with Linux, shell scripting

Nice To Haves

Previous startup experience strongly preferred
Experience implementing applications on Google Cloud Platform
Experience with deep generative models or graph learning a plus.
Tag your application with your solution to an active / recently concluded Kaggle competition, to get ahead of the list :)
Experience leading a team of data and data scientists; Strong ability to multiply the effect of the team and the team members; excellent written communication; self-starter that can balance sophistication with practicality

Responsibilities

Design and deploy machine learning algorithms for use cases spanning e-commerce, consumer trends, markets, logistics, and new products
Work on real-world consumer data for natural language processing, image classification, time series analysis, outlier detection, user modeling, etc
Work with large unstructured data
Be at the intersection of mathematics, machine learning, business, and computer science and impact millions of users through your work
Multiply the effect of your data science and data team members by building frameworks, tools, and methodologies that the entire team use
Provide thought leadership to a team through high quality write-ups, reviews, and a strong vision grounded in practical experience and a wider industry view