Intel is transforming artificial intelligence by harnessing silicon designed specifically for AI, with end-to-end solutions that broadly span from the data centre to the edge, and tools that enable customers to quickly deploy and scale up. With decades of expertise, Intel uses silicon, software, communications, memory, and storage to create the new technologies that AI demands.

The framework optimisations of Intel AI have found their applications in TensorFlow, Theano and Caffe. Whereas on the hardware side, Intel’s Xeon scalable processors are built specifically to run high-performance AI workloads alongside the cloud and HPC workloads.

Here are 5 jobs where you can be a part of building these technologies by using ML skills:

Graphics Software Intern

A graphics software intern will work for the Core and Visual Computing Group (CVCG) and will be part of the team that is responsible for the architecture, design and development of the CPU core and visual technologies that are crucial to Intel’s system-on-a-chip (SoC) products and key to our datacenter, client and IoT platforms.

Requirements

• Pursuing a Master’s degree in Computer Science or relevant engineering areas.
• C, Python

Apply here

Computer Vision Engineer

A CVE will be implementing deep learning CV algorithms, to solve Automotive, Security and Surveillance, Retail, Robotics, Industrial problems. Will be programming, debugging, testing, validation, documentation and/or deployment of the solution/products along with engineering computing frameworks

Requirements

• Master’s or Bachelor’s degree in Electrical/ECE/Computer Engineering from a reputed university with strong fundamentals in VLSI, Computer architecture, machine learning.
• Coursework in computer architecture with significant project experience in design and verification of logic blocks desired.
• Strong programming fundamentals with project work in C/C, Verilog, scripting languages.

Apply here

Pre-Silicon Verification Engineer

When was the last time you heard such a cool-sounding job? An IP Verification Engineer is responsible for verification of Machine learning accelerator IPs and creating a test plan for Accelerator IP based on ML Algorithms.

And, also develop components like BFMs, Scoreboards, Checkers and integrating them which are used for verification. Creating directed and random tests using Systemverilog randomization and conducting automated validation using scripts is also part of the job.

Requirements

• Bachelor’s or Master’s degree in EEE, ECE or CSE, or equivalent with 3 to 6 years of experience in verification.
• Image processing, Machine learning algorithms.
• Perl/Tcl.
• Strong knowledge in Systemverilog, constraint random stimulus generation, SV Assertions and Verification concepts.
• Hands-on experience in Functional coverage implementation and analysis.
• Experience using OVM/UVM methodologies and any of the bus protocols like AHB, AXI, OCP etc.

Apply here

Deep Learning Software Engineer

The job requires the candidate to design, develop & optimize for deep learning training and inference frameworks. Implement model/data parallel frameworks, parameter servers, data flow based asynchronous data communication in deep learning frameworks and transform computational graph representation of a neural network model. Develop deep learning primitives in math libraries.

Requirements

• Master’s or Bachelor’s degree in Electrical/ECE/Computer Engineering from a reputed university with strong fundamentals in VLSI, Computer architecture, machine learning.
• Coursework in computer architecture with significant project experience in design and verification of logic blocks desired.
• Strong programming fundamentals with project work in C/C++, Verilog, scripting languages.

Apply here

Machine Learning SW Architect

ML Architect plays a key role in building products/solutions, which provide descriptive, diagnostic, predictive, or prescriptive models based on data by using machine learning algorithms which requires decent understanding of supervised and unsupervised learning, deep learning, reinforcement learning, Bayesian analysis and others, to solve applied problems in various disciplines such as Data Analytics, Computer Vision, Robotics, etc and hence requires relevant experience.

Requirements

• Masters or PhD in Computer Science or closely related areas with 12 years of experience
• Strong base in ML/DL algorithms

The Client Computing Group, which this role of an architect is part of, is responsible for all aspects of the client computing business across Phone, Phablet, Tablet and PC platforms, leading Intel’s efforts to transform client computing through technologies, new form factors, and driving Intel’s corporate-wide user experience initiatives. This spans all client device brands including hardware, software and connectivity ingredients for phones, tablets, Ultrabook™, All-in-Ones, 2 in 1 computing devices, and home gateways.

Apply here