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Senior Software Engineer, Machine Learning

Employer
Kettle
Location
Berkeley, California, US
Salary
Competitive
Closing date
Oct 4, 2022

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Sector
Academic / Research
Field
Conservation science
Discipline
Climate Change
Salary Type
Salary
Employment Type
Full time
Job Description
The Organization

Kettle's mission is to balance risk in a changing climate. Kettle uses deep learning and proprietary algorithms to reshape the reinsurance industry and better protect people from the growing risks associated with climate change. Kettles first product protects Californians businesses, homes, and livelihoods with wildfire reinsurance. To learn more, visit ourkettle.com

You probably have never heard of the $300bn reinsurance industry, but it is the single most important industry in the world to protect ourselves and help society recover from the effects of climate change disasters. This industry is failing due to a 3x increase in $1B+ crises caused by climate change. Kettles aim is to use deep learning to ensure that peoples lives are not destroyed when these events happen. By building the most sophisticated machine learning models to predict when and where wildfires happen, Kettle accurately prices the cost of covering wildfire prone areas in California. We are a machine-learning-powered reinsurer, in that we sell reinsurance to insurers, we don't sell software to reinsurers.

Who we are/what we value:
  • Obsessive Fanatics - We obsess over big problems. We are fanatical about our business/mission. We drive the company towards the areas people describe as impossible to understand or stop
  • Initiative - Obsessive people dont need micromanagement.
  • Data Focused - With the world burning worse every year, we cant afford opinions and bias to derail data driven decisions.
  • Questioning Renegades - We work in a 600 year old industry. If everyone is running one direction, we generally sprint in the other.
  • Impact Driven - We are a mission driven business


Role

We are looking for a dedicated Software Engineer to join our Machine Learning and Engineering team. You will work with a growing team of engineers, deep learning experts, and other data scientists to model risk using the most advanced tools available. At Kettle you will:

  • Deploy and maintain data pipelines for training, scoring and testing machine learning models.
  • Work closely with cross functional teams (climate and data scientist) to develop, adapt, improve and scale machine learning models.
  • Code deliverables in tandem with Engineering team.
  • Work with diverse data formats with varying data quality
  • Explore the data space to constantly improve the quality of data sources

Requirements

Minimum qualifications:
  • Bachelors degree in Computer Science, related technical field or equivalent practical experience
  • 4 years software development experience
  • Experience in applied machine learning
  • Expertise with at least one general purpose programming language, especially Python.

Preferred Qualifications:
  • Experience in large scale scientific and research data sources
  • Experience with relevant technologies (SageMaker, TensorFlow, XGBoost, machine learning libraries)

Location:
  • Americas only

Benefits

We offer a competitive package that is based on location and experience. We also offer the following benefits:
  • Stock: Ownership in a fast-growing venture-backed company.
  • 401k matching: We care about your ability to save for your future.
  • Family Focus: Parental leave and flexibility for families.
  • Time Off: Flexible vacation policy to encourage people to get out and see the world.
  • Healthcare: Platinum level Medical, dental, and vision policies.
  • Goodies: Whatever hardware and software you need to get the job done.
  • Team Fun: Regularly scheduled events, annual retreat, and celebrations.
  • Learning: Learning & Development Opportunities to grow your skills and career.
  • Great team: Working with fun, hard-working, kind people committed to making a difference!
  • Flexible culture: We are results-focused. We dont work at the office every day.
  • ...And much more! Lots of other perks make this company an incredible place to work.

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