who we are

This is Big.
Big Models, Big Data, and Big Precision.

Neural Magic is re-engineering how deep learning is done. A team of pioneers, we are building a software engine to unlock the potential of machine learning and break free of the limitations of hardware accelerators.

This is Big.
Big Models, Big Data, and Big Precision.

Neural Magic is re-engineering how deep learning is done. A team of pioneers, we are building a software engine to unlock the potential of machine learning and break free of the limitations of hardware accelerators.

Want to bring machine learning back on track?

We're Hiring

Neural Magic is a stealth mode venture-backed software company pioneering a revolutionary new way of running deep learning algorithms efficiently without the need for specialized hardware accelerators. Founded by an award winning team of professors and students out of MIT, we are headquartered in Davis Square, Somerville, MA. We are looking for exceptional, energetic people to join our team.

To apply, please send us your cover letter, CV, and desired position to jobs@neuralmagic.com

SOFTWARE ENGINEER

We are looking for engineers excited to work with parallel and concurrent algorithms, who want to work closely with the founding team and who want to contribute to solving challenging technical problems.

PRIMARY JOB REQUIREMENTS

  • 2+ year of experience coding in modern C++ and writing C++ libraries, writing high performance code for compute intensive operations
  • Low level systems developer (x86 assembly) and multicore programming
  • Experience working with parallel and concurrent algorithms
  • Familiarity with deep neural network models and techniques
  • Likes dynamic work environment
  • Likes to learn new technology concepts

COMMUNICATION & CULTURE

  • Self-directed practitioner who learns fast and is comfortable operating a blank slate environment
  • Strong communications skills with both technical and non-technical team members
  • Strong sense of project ownership and personal responsibility
MACHINE LEARNING SOLUTIONS LEAD

We are a seeking a data scientist excited to work with state-of-the-art deep models, as well as with parallel and concurrent algorithms. This person will work close with our technical team and our customers, bringing deep learning product requirements to our engineers and helping our customers achieve performance benefits with our software. If you are someone who want to contribute to solving challenging technical problems at the forefront of machine learning, this is the role for you.

WHAT YOU’LL DO

  • Work closely with customers to build, refine, train and deploy their neural network models using industry leading frameworks and Neuralmagic’s software
  • Run machine learning experiments to analyze the performance of new techniques and approaches
  • Implement algorithms against our company software, on behalf of customers or in support of product initiatives
  • Understand and report on new research results in the field of deep learning
  • Collaborate with multiple developers about market requirements, best practices and how machine learning is deployed in the wild
  • Be a trusted advisor and partner, providing deep analysis of deep learning approaches, helping to define and conduct pilot tests

WHAT YOU’LL NEED

  • Master’s or PhD degree in math, engineering, or other quantitative discipline
  • Solid knowledge of machine learning fundamentals, in particular CNNs
  • Experience writing, running, testing machine learning models
  • Proficient with Tensorflow and Keras, Pytorch, Caffe and other machine learning frameworks
  • Proficient with leading CNN models including Resnet, VGG and more
  • Experience with Python or R to access large amounts of data, execute multiple analysis steps, visualize intermediate and final results
  • Self-directed individual who learns quickly and is comfortable operating in a blank slate environment
  • Excellent communication skills, ability to tailor technical information for different audiences
  • Strong sense of project ownership and personal responsibility