Machine Learning Lead Engineer at UNCOMN LLC in St Louis, Missouri

Job Description:

UNCOMN is an award-winning firm, one of the country's fastest-growing and--more importantly--a consistent 'Top Workplace' as evaluated by our own employees. We are a values-driven organization (see the Core Values section of our web site) looking for new Uncommon Geniuses to join our growing team. If you are an engineer, architect, analyst, hacker, and/or geek who likes to solve problems, fix things, build things, tweak things, or otherwise show creative flair, you might just be an "UNCOMN Genius."

Our mission is to empower systems thinkers to create elegant solutions to complex problems - to improve the systems that improve our communities. Our team members apply their natural curiosity and grit to discover elegant solutions for our clients' most complex organizational, logistics, process, data, and technical challenges, with the overall goal of building great businesses that contribute to great communities.

Check out our Glassdoor employer reviews, here, and the specifics of this position, below:

UNCOMN is seeking a Machine Learning Lead Engineer to:

·Researches, develops, and implements machine learning algorithms for use in software and hardware applications.
·Maintains up-to-date knowledge of current technological standards, equipment, and practices.
·Identifies and suggests optimizations and features to improve hardware/software capabilities.
·Hypothesizes, writes, and tests machine learning (ML) algorithms and software components to find state of the art solutions for an organization.
·Researches how machines and humans interact and translates that research into improved customer experiences with AI (artificial intelligence).
·Guides transitioning of an algorithm from proof-of-concept to high-performance production model.
·Codes novel, production-level, reusable, interpretable models in R, Python, Java, C++, Scala, SQL, or other languages.
·Collaborates on code reviews and provides technical feedback to improve existing ML model performance.
·Implements innovative natural language processing (NLP), computer vision (CV), decision networks, neural networks, autonomous systems, and other ML-based regression and classification techniques.
·Hypothesizes, writes, and tests machine learning (ML) algorithms and software components to find state of the art solutions for an organization.
·Researches how machines and humans interact and translates that research into improved customer experiences with AI (artificial intelligence).
·Guides transitioning of an algorithm from proof-of-concept to high-performance production model.
·Codes novel, production-level, reusable, interpretable models in R, Python, Java, C++, Scala, SQL, or other languages.
·Collaborates on code reviews and provides technical feedback to improve existing ML model performance.
·Implements innovative natural language processing (NLP), computer vision (CV), decision networks, neural networks, autonomous systems, and other ML-based regression and classification techniques.
·Identify opportunities for data science to improve current products and practices for business and engineering teams. Create machine learning algorithms to optimize and deliver results by reducing computational complexity and increasing the accuracy of models and improving on business metrics. Develop machine learning infrastructure and data pipelines that improve data quality.
·Build and integrate end to end lifecycles of large-scale, distributed machine learning systems using the latest open source technologies
·Develop scalable tools and services for handling machine learning workflows
·Implement cloud distributed training approaches for deep learning models
·Collaborate with engineers across functions to solve complex data problems at scale
·Identify and evaluate new patterns and technologies to improve performance, maintainability and elegance of our machine learning systems
·Design software architecture and data flows for scalable machine learning development work