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- Tasks: Conduct cutting-edge research in computer systems and AI infrastructure with a dynamic team.
- Company: Join a forward-thinking company at the forefront of telecommunications and AI innovation.
- Benefits: Enjoy opportunities for remote work, professional development, and collaboration with industry experts.
- Why this job: Make a real impact through research while enhancing your skills in a supportive environment.
- Qualifications: Bachelor's or Master's in Computer Science; PhD preferred; strong programming and communication skills required.
- Other info: Ideal for recent graduates eager to gain industrial research experience.
The predicted salary is between 36000 - 60000 £ per year.
Research Scientist – Systems & AI Infrastructure
Research Scientist – Systems & AI Infrastructure
We are looking to hire several contract Research Scientists with expertise in computer systems and AI infrastructure to conduct cutting-edge research at the intersection of computer systems, machine learning, and distributed systems. These roles are ideal for recent PhD graduates seeking industrial research experience, or for exceptional B.Sc. or M.Sc. graduates looking to deepen their research skills in an industry setting. We welcome applicants with backgrounds in one or more of the following areas: operating systems, distributed systems, and machine learning systems.
Key Responsibilities:
- Rapid Prototyping: Collaborate with a multidisciplinary team to quickly develop and test proof-of-concept prototypes, validating research ideas in real-world, industrial environments.
- Performance Optimization: Perform detailed profiling and optimization of operating systems and large-scale distributed systems, leveraging a range of heterogeneous hardware (e.g., CPU, NPU) for enhanced performance.
- Research Publications: Transform research findings and innovative contributions into high-impact publications in top-tier academic journals and conferences.
- Technical Documentation: Create and maintain comprehensive technical documentation outlining research methods, design decisions, and implementation specifics to ensure reproducibility and support internal knowledge sharing.
- Stakeholder Engagement: Communicate research progress, performance insights, and key outcomes to internal stakeholders through clear and engaging presentations.
Required:
- Bachelor\’s or Master\’s degree in Computer Science or a related technical field.
- Be comfortable with research methodology.
- Have an in-depth understanding of operating systems and/or distributed systems and/or cloud computing and/or machine learning algorithms.
- Good programming skills, master of at least one language, such as C/C++.
- Good communication and teamwork skills.
- PhD in operating systems, distributed systems, machine learning, or a related field.
- Published papers in top journals/conferences focused on systems (NSDI, EuroSys, SoCC, OSDI etc.) and/or machine learning (NeurIPS, ICML, ICLR).
- Experience in the full lifecycle of developing, deploying, and maintaining large-scale cloud production systems, demonstrating expertise in scalability, reliability, and performance optimization.
Seniority level
-
Seniority level
Not Applicable
Employment type
-
Employment type
Full-time
Job function
-
Job function
Research
-
Industries
Telecommunications
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Research Scientist - Systems & AI Infrastructure employer: Project People
Contact Detail:
Project People Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist - Systems & AI Infrastructure
✨Tip Number 1
Make sure to showcase your hands-on experience with rapid prototyping. Highlight any projects where you've collaborated with teams to develop proof-of-concept prototypes, as this is a key responsibility for the role.
✨Tip Number 2
Familiarise yourself with the latest trends in performance optimisation for operating systems and distributed systems. Being able to discuss recent advancements or techniques during interviews can set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your research publications in detail. Be ready to explain your contributions and how they relate to the fields of systems and AI infrastructure, as this will demonstrate your expertise and commitment to the field.
✨Tip Number 4
Practice your communication skills, especially in presenting complex technical concepts clearly. This role requires engaging with stakeholders, so being able to convey your research progress effectively will be crucial.
We think you need these skills to ace Research Scientist - Systems & AI Infrastructure
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in computer systems, machine learning, and distributed systems. Emphasise any projects or research that align with the key responsibilities of the role.
Craft a Strong Cover Letter: Write a cover letter that specifically addresses the job description. Mention your academic background, relevant skills, and how your research aligns with the company's goals. Be sure to express your enthusiasm for the position.
Highlight Research Publications: If you have published papers, list them prominently in your application. Focus on those that are relevant to operating systems, distributed systems, or machine learning, as these will strengthen your candidacy.
Showcase Technical Skills: Clearly outline your programming skills, especially in languages like C/C++. Include any experience with cloud production systems and performance optimisation, as these are crucial for the role.
How to prepare for a job interview at Project People
✨Showcase Your Research Experience
Be prepared to discuss your previous research projects in detail. Highlight any publications you've contributed to, especially those in top-tier journals or conferences related to systems or machine learning.
✨Demonstrate Technical Proficiency
Make sure you can talk confidently about your programming skills, particularly in languages like C/C++. Be ready to discuss specific projects where you've optimised performance in operating systems or distributed systems.
✨Engage with Stakeholders
Practice explaining complex technical concepts in a clear and engaging manner. You may be asked to present your research findings, so think about how you would communicate these insights to non-technical stakeholders.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities. Be ready to tackle hypothetical scenarios related to rapid prototyping or performance optimisation, demonstrating your analytical thinking and creativity.
