Job Description

Company Description*
What We Do*
Miratech helps visionaries to change the world. We are a global IT services and consulting company that brings together global enterprise innovation and start-up innovation. Today we support digital transformation for the largest enterprises on the planet.
By partnering with both large and small players, we stay at the leading edge of technology, remain nimble even as a global leader, and create technology that helps our clients further enhance their business. Our culture of Relentless Performance enables over 99% of Miratech's engagements to succeed by meeting or exceeding scope, schedule and/or budget objectives since our inception in 1989.
As a backend ML engineer, you will sit on a product team developing AI, ML, and optimization products that are of strategic importance to the firm. You will partner with our product managers, researchers, and stakeholder teams to develop production-grade model implementations and infrastructure that facilitate the use of our models and analytics within a larger, integrated workflow. This includes implementing the methods being developed by the researchers in production-grade code and building surrounding infrastructure such that the analytics may be accessed via a variety of access patterns (API, files, etc.). You will also be responsible for creating automated tests of all software developed, including unit and integration tests.
Responsibilities:

• Accurately implement methods described in technical documentation developed by our researchers.
• Develop accompanying infrastructure to make the models and analytics developed accessible via a variety of access patterns.
• Test all software being developed for accuracy and stability.

Qualifications

• A bachelor's, master's, or Ph.D. in computer science or similar software engineering-focuseded major. A second major, minor, or degree in an adjacent quantitative discipline, such as math, engineering, or physics is a big plus.
• 2+ years of professional experience implementing machine learning models, optimizers, and other quantitative tooling in a professional setting.
• The ability to read and understand mathematical documentation in the form of whitepapers containing the methods being developed.
• Proficiency in Python in the contexts of automation, infrastructure development, and quantitative computing.
• Strong understanding of Python scientific libraries such as Numpy, Scipy, Pandas, PyTorch, etc.
• Understanding of testing in the context of software engineering, including unit testing, integration testing, performance testing, etc.
• Background in finance will be looked upon favorably but is not a requirement.

Additional Information*
We offer*

• Strong career opportunities for professionals
• A variety of international projects and mobility across projects
• Professional development support and professional certification opportunities
• Competitive compensation, advanced bonus systems
• Flexible working schedule with a remote possibility
• Corporate, social and cultural events

Job Type: Full-time