MarkiTech Hiring for AI ML System Software Engineer at Toronto, ON Full Time

Job Overview:
Background: AI is transforming everything. We are making AI ubiquitous. Today, more intelligence is moving to edge devices, and mobile is becoming the pervasive AI platform. Building on the smartphone foundation and the scale of mobile making AI ubiquitous – expanding beyond mobile and powering other end devices, machines, vehicles, and things. We are inventing, developing, and commercializing power-efficient on-device AI, edge cloud AI, and 5G to make this a reality.

We are looking for talented and passionate engineers to develop and deliver AI/ML solutions across multiple domains including:

AI/ML Systems: Develop Compiler toolchain to enhance the performance of the ML compiler and contribute to future evolution of the AI SW/HW solutions.

AI/ML Software: Develop new tools and SDKs to extend our AI solutions into all industry leading customer use cases.

AI/ML Apps: AI/ML Application/Use-Case Architect and system software developer and test engineers for low power, high performance machine learning application development and analysis.

ALWAYS-ON AI Software: Develop toolchain and software stack for low power embedded neural engine on Snapdragon. Enable and optimize the performance of voice assistant and always-on camera use cases.

For AI/ML System Engineers:
Define and implement efficient ML compiler algorithms that map workloads to Qualcomm HW for different product segments

Analyze ML/AI workload performance and power on Qualcomm HW and determine cost-effective methods of improving these metrics.

Create and drive flow to monitor evolving on-silicon performance to discover root-cause and remedy discrepancies between observed versus architectural models.

Contribute to software quality by improving efficiency, scalability, and stability of the compiler tool chain.

Understand trends in ML network design, through customer engagements and latest academic research, and determine how this will affect both SW and HW design

For AI/ML Software Engineers:ML SW Engineers:
Development of optimization algorithms for ML operators/layers for the Qualcomm AI SW stack

Development of AI systems optimizations to maximize utilization of Qualcomm AI HW and SW

Enabling and optimizing state of the art neural network models to meet the demands of customer real world use cases

Development of software tools for profiling, and debugging to support rapid deployment of new neural networks in this fast changing field

Extend your experience as a seasoned SW engineer to deliver commercial quality software releases

ML SW Verification Engineers:
Testing framework development for Qualcomm Machine Learning Software stacks validation

Maintain and improve ML SW automation test framework

Test plan and test case development from the feature requirements and use case analysis

Supporting multiple teams for automation testing setup

Working closely with development team for regression report triage, bug analysis and issue tracking

For AI/ML Apps Engineers:
Application/Use-Case Architect – for low power, high performance machine learning application development and analysis

Modelling DSP and Neural Network Accelerators, event driven modelling of end-to-end use-cases, developing tools to facilitate the use-case modelling and helping to analyze machine learning and traditional AI based applications.

Perform HW/SW Use-Case Mapping and Partitioning – provide recommendations about how to best map compute intensive algorithms to run on Qualcomm’s AI/ML processor.

Developing and Optimizing Vector DSP code for the Qualcomm’s AI/ML Processor using C/C++

Perform competitive analysis and customer support

Systems SW Engineer – for developing embedded machine learning software applications and use cases developed for Qualcomm Snapdragon processors.

The candidate will work on implementing new cutting-edge algorithms in the areas of machine learning, computer vision and video processing that bring artificial intelligence to mobile and edge devices. Responsibilities include software design, development, integration, test, and support of these applications for the Qualcomm Hexagon DSP.

Software test Engineer – for design and integration of leading edge technologies in the area of Image post processing, 360 Video, Virtual Reality, Computational Imaging, Machine learning, Deep Convolution Networks, Computer Vision, Drones, IoT, Driverless cars and many more.

Lead and develop test strategies covering both functional and non-functional capabilities, for designed SW features, by devising test acceptance criteria, formulate test cases and implement test automation capabilities

Lead, develop and maintain test infrastructure, including the test framework and environment, and associated automation tools and test environment setup

Provide active technical leadership for the test-to-release lifecycle, including perform tests automation, analyze test results and investigate issues, and tracking and communicating with the project team on defects, issues, and status

Work with SW development teams to incorporate the SW feature and any updates into the test platform

Actively work on identifying improvement areas for testing and contributing to increasing the testing efficiency

ALWAYS-ON AI Software

Development of end-2-end embedded AI SW stack to run neural network models on Qualcomm leading edge hardware with optimal resource usage

Design and enhance the implementation of ML/AI compilers, kernels, and runtime software to improve performance and power efficiency

Collaborating with AI Processor Hardware team and high quality implementation of new ML operators/layers to optimal utilizing new capabilities in next-gen AI processor

Development of debugging/profiling tools and user-friendly SDK for customers to rapid deployment of their new use cases

Challenging the status quo and driving innovations to be the best-of-class

Minimum Qualifications:
Education: Bachelors – Computer Science, Bachelors – Engineering, Bachelors – Information Systems

Experiences:
Senior Engineering positions: 2+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

Staff engineering positions: 4+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

Sr. Staff Engineering positions: 5+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

Principal Engineering positions: 10+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

Excellent programming skills in Python, C/C++

Understanding of vector programming concepts

Understanding of computer architecture

Understanding of hardware architecture

Preferred Qualifications:
Education: Bachelor’s degree in Computer Engineering, Computer Science, Electrical Engineering or related area

Experiences:
Senior Engineering positions: 4+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

Staff engineering positions: 6+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

Sr. Staff Engineering positions: 8+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

Principal Engineering positions: 20+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

For AI/ML System Engineers:
Ability to code in C++ and Python

Strong software engineering principles are essential

Strong background in algorithm development and analysis

Exposure to front-end ML frameworks (i.e. TensorFlow, PyTorch, ONNX)

Exposure so SW and/or HW verification/validation flows.

Experience in compiler design and development is an asset.

Knowledge of different classes of ML models (i.e. CNN, RNN, Transformers, etc.) is an asset

For AI/ML Software Engineers:
Experience with C/C++ development

Some experience with Python and Git

Android or embedded Linux software development

Experience with Python numpy and deep learning frameworks such as Caffe, Caffe, TensorFlow, PyTorch

ML SW Engineers:
Live and breathe software development with excellent programming capability and analytical, development, and debugging skills

Optimizing algorithms for hardware acceleration cores using OpenCL, OpenGL ES, and / or DSPs

Background in mathematical operations: linear algebra, fast math libraries, multi-threading and vector instruction sets

ML SW Verification Engineers:
SW testing/development experience

Strong problem solving and debugging skills

Solid understanding of SW development cycle and testing methodologies

Experience with embedded system programming and/or testing

Experience with:
Shell and other scripting language

Jenkins and other CI tools

Static code analysis and code coverage tool

For AI/ML Apps Engineers:
Machine learning algorithms;

Image and video processing and computer vision algorithms;

Application/Use-Case Architect – understanding of / experiences with:

Operating systems concepts such as synchronization and memory management;

Computer architecture

Hardware architecture

Machine learning frameworks like TensorFlow and Pytorch

Strong motivation and capabilities in learning new subjects especially in the field of artificial intelligence

Test Engineer:
Strong Linux programming skills with experience in C/C++, scripting languages (Perl/Python), and build systems

Strong knowledge of configuring and deploying automation servers (Jenkins)

Strong knowledge of CD/CI and designing CI workflow

Strong problem-solving skills

Experience working with source control management (Github/Gerrit/Perforce)

Experience working with containers (Docker, Kubernetes) a plus

Knowledge of the ARM development environment a plus

Knowledge of embedded development a plus

Knowledge of Java/Android and open source is a plus

For AI/ML Proc Sys Engineers:
Excellent programming capability with C/C++

Strong software design, development, and debugging skills

Optimized Linux, Android, or embedded software development experience

Optimization of algebraic operations in algorithms for HW cores

Experience on compiler design and development is a big plus

Knowledge on deep learning and popular frameworks is an asset

Minimum Qualifications

Education:
Bachelors – Computer Science, Bachelors – Engineering, Bachelors – Information Systems

Work Experiences:
5+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

Skills:
Preferred Qualifications

Education:
Masters – Computer Science, Masters – Engineering, Masters – Information Systems

Work Experiences:
5+ years experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++) ,5+ years experience using statistics and probability (e.g., conditional probability, Bayes rule) ,5+ years experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media) ,5+ years experience with Machine Learning frameworks (e.g.,Tensor Flow, Caffe, Caffe 2, Pytorch, Keras). ,3+ years of experience working in a large matrixed organization.

Skills:
AI Frameworks, Calculus, Data Manipulation, Deep Learning, Machine Learning, Performance

Apply at [email protected]