Machine Learning Engineer | MLE, Cyber Risk Analytics- CANADA- (REMOTE OPTION) at Cyence | Powderkeg

Location: Canada - Remote

Employment Type: Full-time

Team: Analytics and Data Services

Ready for a new challenge? Join Guidewire as a Machine Learning Engineer! We would love to see your background! Our Machine Learning team here at Guidewire is responsible for building Machine Learning Systems and Tools that make Guidewire products more intelligent and helps deliver analytics at scale. We are constantly faced with results-oriented challenges in the areas of Natural Language Processing, Deep Learning, Risk Modeling and Operational Analytics.

**Who We Are, What We Believe, & What We Build **

Guidewire is the AWS of insurance. As the market leader, 380 insurance companies run on our critical platform. Every second, we support underwriters crafting policies and agents settling claims. We believe that making a great decision should not require 100 in-house data scientists. Our products range from cyber risk quantification to potent ML sandboxes. We are a post-IPO company with the vision to redefine insurance. There is a lot to be done.


  • Define, models and solve real world, ambitious, insurance problems using various data-driven approaches.
  • A passion for Designing, building, and testing models and deploying them into production.
  • Design and implement tools and frameworks to be used across various machine learning and data science teams.
  • A strong desire to help build the next generation Machine Learning platform that will be used by internal and external Guidewire customers.
  • Identify areas where we can apply Machine Learning at Guidewire and work with product managers and domain specialists to produce and end to end solution.
  • Work in a fast-paced Agile/Scrum environment to help us deliver high quality software.


  • Advanced Degree in Computer Science, Engineering, Mathematics or a related field.
  • 2+ years of validated experience in a data science or ML engineering role.
  • Solid understanding of ML techniques (parametric and non-parametric models, clustering, anomaly detection, evaluation metrics, interpretability methods).
  • Experience with at least one ML modeling framework such as Tensorflow or Pytorch.
  • Curiosity and internal motivation to constantly improve
  • Experience with Amazon AWS services such as EC2, EMR, S3, SageMaker.
  • Experience building and productionizing end-to-end machine learning pipelines.
  • Strong communication skills, a collaborative mindset, curiosity, and internal motivation to constantly improve.


  • Huge plus if you have experience working with big data tools & orchestration tools such as Spark, Airflow and K8
  • Strong knowledge of groundbreaking NLP models like LSTMs and Transformers
  • Strong knowledge of statistics, probability, and building scalable Monte Carlo Simulation-based models.
  • Experience with Infrastructure as Code is a huge plus
  • Highly motivated to learn more about Cyber Security and the P&C insurance industry


#machinelearning #aws #sagemaker #propertyandcasualty #datamodeling #pytorch #tensorflow #python #sql #cyber #iaac #nlp #engineer #gudewire

About Guidewire

Guidewire is the platform P&C insurers trust to engage, innovate, and grow efficiently.

Guidewire combines core, data, digital, analytics, and AI to deliver our platform as a cloud service. More than 400 insurers, including the largest and most complex in the world, run on Guidewire.

As a partner to our customers, we continually evolve to enable their success. We are proud of our unparalleled implementation track record with 1000+ successful projects, supported by the largest R&D team and partner ecosystem in the industry. Our Marketplace provides hundreds of add-ons that accelerate integration, localization, and innovation.

Guidewire Software Inc. provides equal employment opportunities to all applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. All offers are contingent upon passing a criminal history and other background checks where it's applicable to the position.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Job Summary
  • Job Title
    Machine Learning Engineer | MLE, Cyber Risk Analytics- CANADA- (REMOTE OPTION)
  • Company
  • Location
    San Mateo, CA
  • Employment Type
    Full time
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