Software Engineer

U.S. Benefits

What are some of the benefits and perks of working at MathWorks?

– 401(k) matching

– Quarterly profit-sharing plan

– Tuition reimbursement

– Paid Volunteer Time

– Fitness and Recreation

– Wellness center

– Training and Development

– Relocation Assistance Provided

MathWorks has a hybrid work model that enables staff members to split their time between office and home. The hybrid model provides the advantage of having both in-person time with colleagues and flexible at-home life optimizations. Learn More: https://www.mathworks.com/company/jobs/resources/hybrid-model.html.

Working under the direction of the Manager or Senior Team Lead, will be responsible for designing and developing sophisticated software; developing software to improve the interoperation between MathWorks Deep Learning Toolbox with third-party platforms — TensorFlow/Keras, PyTorch and ONNX; developing and supporting machine learning applications and algorithms for code generation, performance, and visualization; designing, developing and maintaining connections with third-party deep learning software; creating additional network layers to support model sharing with other frameworks; participating in customer interviews, usability tests, prototyping, and design reviews; developing appropriate architecture and implementation; participating in all team activities including team planning, design discussions, and reviews; and working effectively with other teams to provide a quality product for customers.

MathWorks nurtures growth, appreciates diversity, encourages initiative, values teamwork, shares success, and rewards excellence.

Minimum Qualifications:

Education and Experience:

Master’s degree in Engineering, Computer Science, or a closely related field (or foreign education equivalent) and no experience.

Special Requirements:

• Demonstrated expertise programming in C++, Python and MATLAB, including object-oriented design and analysis in MATLAB and C++ according to design patterns and data structures.
• Demonstrated expertise designing and developing software to inter-operate with third party deep learning frameworks — TensorFlow and PyTorch.
• Demonstrated expertise applying statistical methods — linear algebra, probability, and mathematical optimization — and machine learning methods — classification and regression — to build statistical tools and machine learning applications.
• Demonstrated expertise in the full software development life cycle (SDLC), including functional design, architecture design, implementation, and testing.

[Expertise may be gained during Graduate program.]