Benefits Offered

401K, Dental, Life, Medical, Vision

Employment Type


Job Overview

At Breville, we develop innovative appliances to help customers make better food and drinks. We are looking for an individual who will collaborate with teams of engineers and designers to leverage math and physics to solve difficult challenges. He/she will use math and physics to interpret the design and engineering challenges; this individual will formulate the challenge in mathematical terms and use a variety of mathematical and computational tools to explore possible solutions; and work closely with teams to help them implement these solutions. Often you will develop algorithms and mathematical software to enhance the performance of appliances to help customers make better food and drinks.

Essential Responsibilities
- Collaborate on hard problems that will make people happy
- Develop innovations that lead to patents and other intellectual property
- Design and implement algorithms in Python and a complied language (such as C, C++, or Fortran), and
- Use physics-based and Bayesian modeling to solve complex problems
- Focus on the use and development of mathematical tools, rather than traditional statistical theory or engineering tools, to support and advance controlling and designing cooking appliances

-Interpret data and report conclusions from this analysis

-Use data to support and improve business decisions

Minimum Qualifications
- PhD in applied math, physics, electrical engineering, computer science, mathematics, and/or other quantitative focused degree
- 2+ years of relevant experience [outside PhD]
- Proficiency in Python and at least one compiled language (Fortran, C, or C++) with a strong background in scientific computing

Required Qualifications
- Strong critical thinking and an ability to solve problems independently
- Sound math and computer science knowledge
- Collaboration with experts from different fields
- Theoretical and applied analysis of time series, such as Kalman filters
- Experience working with heterogeneous and incomplete data
- Effective collaboration on several simultaneous projects in different geographic regions
- Interdisciplinary skills in math, physics, chemistry, and computer science