UFG offers you an award-winning workplace and a trustworthy, financially stable company. While we’ve always known our commitment to employees and financial stewardship, it is good to have others recognize our dedicated efforts. We've been named an Iowa Top Workplace by the Des Moines Register for four consecutive years, and included on Forbes’ “America’s Most Trustworthy Financial Companies” every year since 2014. Additionally, UFG is a super-regional property and casualty insurer rated “A” (Excellent) by A.M. Best Company.
We are seeking a Senior Machine Learning Engineer who is capable of solving hard data science problems and building the Analytics as a Service ecosystem necessary to deliver those solutions to our customers. We are seeking candidates who enjoy having autonomy in their work, take pride in seeing their work directly impact the lives of others, and are as ambitious as we are in capturing significant market opportunities. The ideal candidate will possess strong technical and communication skills, as well as proven experience in developing and deploying machine learning in a real-time operational environment.
This position can be located at any of our regional UFG Offices or remotely from anywhere in the US.
Collaborate with our data scientists to design, train, and deploy machine learning model
Integrate modelling solutions into our overall technical platform
Architect, develop, and automate data pipelines and systems that reliably support production ML models and model-driven services
Build & maintain a production-ready experimentation platform to run models in parallel
Work with our engineers to deploy scalable infrastructure that support product features, DS/ML R&D projects, and big data analytics services
Prepare and preprocess data in collaboration with the data engineering team
Fine tune performance to optimize user response times and model execution
Strong knowledge of converting the trained model into REST or SOAP APIs to expose as web services
Socialize and mentor other engineers in best practices
Research opportunities for data acquisition and new uses for existing data
Collaborate with data scientists, architects, data analysts and engineers to support technical and product roadmap planning
Competencies typically acquired through a Masters or Ph.D. (in Statistics, Computer Science, Mathematics, or other STEM field of study)
Proven track record of successfully architecting and building highly available, low latency systems for high traffic applications
Experience developing and delivering ML-based services and product features into commercial software applications
Knowledge, skills & abilities:
Intuition on how to architect scalable distributed computing systems for machine learning
Familiarity with machine learning and parallel processing pipelines, experience with implementation in low-latency real-time platforms and/or scalable offline batch processes
Highly proficient in Python and experience using common DS/ML frameworks such as scipy, scikit-learn, TensorFlow/Keras, etc.
Solid foundation of computer science, software engineering, and system architecture design principles
Understanding of data structures, data modeling and software architecture
Knowledge of Hadoop or other distributing computing systems
Ability to write robust code in SQL, Python, and Java
Comfortable configuring, deploying, and managing cloud resources (GCP, AWS, etc) for your projects
Job scheduling technologies and containerization for isolated development shouldn’t be foreign concepts to you
Ability to thrive in a fast-paced environment with significant uncertainty
Pragmatic approach to problem-solving
Desire to always be learning, and a collaborative team-player attitude