Machine Learning Engineer (open to remote)

Company: American Family
Location: Casper
Posted on: June 11, 2021

Job Description:

Location: AF-IL Offsite Illinois
Location: AF-MA Offsite Massachusetts
Location: AF-MN Eden Prairie Office

At American Family Insurance, we believe people are an organization's most valuable asset, and their ideas and experiences matter. From our CEO to our agency force, we're committed to growing a diverse and inclusive culture that empowers innovation that will inspire, protect, and restore our customers' dreams in ways never imagined.

American Family Insurance is driven by our customers and employees. That's why we provide more than just a job - we provide opportunity. Whether you're already part of our team in search of a new challenge or new to our company and ready for what's next, you're in the right place. Every dream is a journey that starts with a single step. Start your journey right here. Join our team. Bring your dreams.

Job ID:
R21394 Machine Learning Engineer (open to remote) (Open)

Compensation may vary based on the job level and your geographic work location.

Compensation Minimum:$88,400 Compensation Maximum:$141,600
Summary:
Join the Machine Learning Research Team at American Family Insurance. The vision of this group is to provide innovative enterprise solutions inspired by ML, AI & data science through state-of-the-art research & assimilation. The research approach combines the art of the possible, product design, enterprise collaboration, and the research community. Research pillars include: Human in the Loop, Document Intelligence, Aerial Imagery, Process Optimization, AI-Based Data Management, & Knowledge Management. External Research Partnerships include: Mila, NIU, Stanford Data Science Consortium, The University of Chicago, National Robotics Engineering Center, and the American Family Insurance Data Science Institute at the University of Wisconsin.

For more information on the team, please visit: https://www.ai-ml-amfam.com/

Job Description:

Primary Accountabilities

• Keeping abreast with the latest advances of the research, tools and datasets of machine learning, deep learning and artificial intelligence.

• Be able to rapidly prototype and test innovative hypotheses resulting in experiments and discoveries that are publication quality.

• Lead or participate in the publication process.

• Building scalable infrastructure that enables training, evaluating, deploying and serving machine learning and deep learning models.

• Design and develop lineage and artifact tracking infrastructure for training data, ML models and reproducible ML Pipelines for orchestrating various components for ML models (Preferable on AWS and Google Cloud Platform).

• Hands-on design and implement machine learning and deep learning software.

• Advocate and liaise across ML research team and engineering teams to promote and support engineering best practices.

• Willing to learn new and emerging tools for machine learning software, pipelines and model deployment at scale.

• Leveraging machine learning, predictive modeling and operational research across a variety of problem domains or business initiatives in insurance, to support business partner objectives and business needs.

• Collaborate with business partners to develop problem definition, analytical approach, and research design for modeling projects.

• Representing team to coordinate and support internal and external machine learning research partners and projects.

Education and Licenses

• Master's Degree in Mathematics, Statistics, Physics, Computer Sciences or Engineering, or related quantitative fields or equivalent experience. PhD degree is a plus.

Specialized Knowledge and Skills Requirements:

• Solid programming skills in C/C++, Java, or Python.

• Familiarity with one or several of the following areas: Natural Language Processing, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation.

• Participate in the research paper writing and publication processes.

• Experience in distributed system design and development.

• Experience in distributed data processing tools e.g. Spark, Kafka.

• Experienced in distributed container orchestration system, e.g. Kubernetes.

• Experience in building scalable software and infrastructure in AWS and/or Google Cloud Platform.

Knowledge of the following areas is a plus:

• Experience in machine learning frameworks such as Tensorflow, Pytorch, Keras, Scikit-Learn etc.

• Experience with GCP Kubeflow, AutoML and AI Platform

• Experience in monitoring the performance of machine learning models at scale

• Experience in scalable cloud infrastructure that enables training, evaluating, deploying and serving machine learning and deep learning models.

Travel Requirements

• This position requires travel up to 10% of the time.

Additional Job Information:

Depending on qualifications, candidates may be considered at different levels.

Offer to selected candidate will be made contingent on the results of applicable background checks.

Offer to selected candidate is contingent on signing a non-disclosure agreement for proprietary information, trade secrets, and inventions.

We are open to hiring candidates to work remotely (anywhere in the USA). However, we are also open to candidates who will relocate to our headquarters location of Madison, WI or in our Seattle, WA or Chicago, IL locations. Relocation assistance may be available.

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When you work at American Family you can expect benefits that support your physical, emotional, and financial wellbeing. You will have access to comprehensive medical, dental, vision and wellbeing benefits that enable you to take care of your health. We also offer a competitive 401(k) contribution, a pension plan, an annual incentive, and a paid-time off program. In addition, our student loan repayment program and paid-family leave are available to support our employees and their families. Interns and contingent workers are not eligible for American Family Enterprise benefits.

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Keywords: American Family, Casper , Machine Learning Engineer (open to remote), Other , Casper, Wyoming

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