Company Overview:

Arturo is an AI property analytics company that helps Insurance Carriers improve the accuracy and speed of decision-making across claims, underwriting, pricing, and renewals. Developed by and for Insurance Carriers, Arturo accesses a wide breadth of claims and policy data to continuously improve the quality of our predictive models and proprietary Confidence Scores. Arturo delivers on-demand property data utilizing multi-source imagery via a configurable API, enabling better risk assessment. 

Position Overview: 

Better. Faster. Cheaper. We’re talking AND not OR. Empowering Fortune 500  customers with timely and accurate property information at scale and on budget is  what we do, and we are looking for your help. If you are passionate about building,  deploying, and maintaining state of the art machine learning solutions, then read on. 

What you’ll do: 

• Iteratively train, evaluate, deploy, monitor, and refresh deep learning models 
• Build and maintain internal software tools aimed at standardizing and  streamlining our modeling pipeline 
• Adhere to software-engineering best practices: testing, code reviews, quality, and performance.
• Scour the latest research papers in search of ideas that can make our  production models better, faster, and cheaper. 
• Challenge and be challenged on a diverse, collaborative, and brilliant team
• Demo models, write company blog posts, and share your favorite new tools,  techniques, and libraries with the team. 

What you bring: 

• Passion for writing well-documented, tested, and production-ready code
• Thorough understanding of deep learning concepts and APIs 
• Professional and demonstrable experience training, evaluating, deploying, and  monitoring deep learning models 
• Proficiency with the following tools: Python, NumPy, TensorFlow and/or  PyTorch, at least one Python testing framework, and Docker 
• Seamless ability to collaborate closely with product and software engineers to  ensure customer requirements are met and on-time 

Nice-to-haves: 

• Familiarity with AWS and Kubernetes 
• Experience with OpenCV and/or scikit-image 
• Exposure to geospatial data and tools 
• Familiarity with nuances of designing and managing projects requiring human  annotators 
• Insurance and/or geospatial domain expertise

Successful Machine Learning Engineers will: 

• Ideate, build, and integrate a new model or product into the Arturo production  system 
• Refresh an existing deep learning model with one that is more performant,  produces faster inferences, requires less expensive compute 
• Develop a new proprietary tool that the internal machine learning team can  leverage to enhance current product offerings or improve current modeling  processes 
• Manage the numerous complexities and competing interests required to  develop a monetizable product offering 
• Communicate model limitations, potential enhancements, and associated  timelines 

Why you want to work here: 

• You want to solve challenging ML problems that advance the state of the art 
• You are excited about building and maintaining deep learning solutions at  scale 
• You relish working alongside passionate, respectful, and intelligent teammates 
• You enjoy being challenged by those around you to achieve great things 
• You take pride in your work and want to see results provide tangible value 
• Fortune 500 customers will use the outputs of your models to power their  business and make decisions 

What you’ll learn:  

• State of the art ML models and techniques 
• Best practices for implementing and designing production-ready ML products 
• Hard and soft skills that will make you a better engineer, strategizer, and leader 
• An efficient framework for converting business ideas into monetizable  products 

Arturo is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.