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    Research Scientist at Intel - United Kingdom - Serendeputy

    Serendeputy
    Serendeputy United Kingdom

    2 weeks ago

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    Description

    Job Details:

    Job Description:

    Supports software development and engineering of new artificial intelligence, machine learning, and deep learning products and technologies for the enterprise through research, leading to new or improved software products. Researches technological trends and advancements, recommending strategic product enhancements to ensure product relevancy and support revenue growth. Collaborates with industry and academies, participates in industry standard definition, collaborates with product managers and technical groups to address important customer issues, and finds innovative solutions to difficult problems for midterm or longterm time frames. May research to define boundaries, create proof of concepts, or prototype new ideas.

    Qualifications:

    You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. Experience would be obtained through a combination of prior education level classes, and current level school classes, projects, research, and relevant previous job and/or internship experience.

    Minimum Qualifications:
    The candidate must have a Master's Degree or Ph.D. degree in Computer Science, Electrical Engineering, Computer Engineering, Physics, or other related areas. The candidate must have completed coursework in programming language design, compilers or code generation. 3+ years of experience in below areas:
    • Solid software development skills in C++.
    • Foundational knowledge of hardware architecture
    • Experience on open-source compiler infrastructures or published papers on compilation technologies.

    Preferred Qualifications:

    • Good understanding of instruction set architecture, memory hierarchy, profiling and identifying performance bottlenecks.
    • Experience with LLVM/MLIR optimization infrastructure, code transformation and generation.
    • Existing upstream contributions into LLVM projects, preferably MLIR.
    • Demonstrated experience in parallel workloads (e.g., machine learning, scientific computing, data analytics)
    • Tier-1 publications

    Job Type:

    Experienced Hire

    Shift:

    Shift 1 (United Kingdom)

    Primary Location:

    Virtual United Kingdom

    Additional Locations:

    Virtual France, Virtual Italy, Virtual Switzerland

    Business group:

    Intel Labs is the company's world-class, industry leading research organization, responsible for driving Intel's technology pipeline and creating new opportunities. The mission of Intel Labs is to deliver breakthrough technologies to fuel Intel's growth. This includes identifying and exploring compelling new technologies and high risk opportunities ahead of business unit investment and demonstrating first-to-market technologies and innovative new usages for computing technology. Intel Labs engages the leading thinkers in academia and industry in addition to partnering closely with Intel business units.

    Posting Statement:

    All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

    Position of Trust

    N/A

    Work Model for this Role

    This role is available as a fully home-based and generally would require you to attend Intel sites only occasionally based on business need. This role may also be available as our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. In certain circumstances the work model may change to accommodate business needs.

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