At a Glance
- Tasks: Design and implement cutting-edge machine learning solutions for scientific research.
- Company: Join Microsoft Research's AI for Science team, transforming scientific discovery with AI.
- Benefits: Enjoy remote work options, industry-leading healthcare, educational resources, and generous time off.
- Why this job: Be part of a collaborative team tackling global challenges like climate change and drug discovery.
- Qualifications: Master's degree in relevant fields and strong experience with machine learning and distributed systems required.
- Other info: No prior high-performance software experience needed, just a passion for pushing scientific boundaries.
The predicted salary is between 43200 - 72000 £ per year.
Responsibilities (Text Only)- Architect, design, and implement scalable and robust solutions for machine learning and scientific research involving large volumes of heterogeneous data. – Build and optimize distributed data processing and model building pipelines. – Develop and maintain tools and technologies for building, training, optimizing, scaling machine learning solutions. – Collaborate with cross-functional teams, including scientists, researchers, and software engineers. – Document and share best practices across the organization. – Maintain the highest standards in code quality and software design.Qualifications (Text Only)Required: – Master\’s degree or equivalent work experience in Computer Science, Physics, Engineering, Chemistry, Mathematics or a related field. – Strong familiarity with Linux and the open-source ecosystem. – Proficient experience working with machine learning and large datasets. – In-depth understanding of open source machine learning frameworks (e.g., PyTorch, ggml, llama.cpp, vllm). – Experience building complex systems on the cloud. – Experience building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs. – Strong analytical, problem-solving, and communication skills. – Passionate about pushing the boundaries of science. Prior experience developing high-performance scientific software is not required, but preferred. #Research #AI for Science Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a requestvia the Accommodation request form. Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work. #J-18808-Ljbffr
Research Software Development Engineer, MSR AI for Science employer: JobLeads GmbH
Contact Detail:
JobLeads GmbH Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Software Development Engineer, MSR AI for Science
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning and AI, especially those related to scientific research. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of AI for Science. Attend relevant conferences, webinars, or meetups to connect with potential colleagues and learn about their experiences. This can provide valuable insights and may even lead to referrals.
✨Tip Number 3
Showcase your collaborative skills by participating in open-source projects or contributing to research initiatives. Highlighting your ability to work in cross-functional teams will demonstrate that you are a good fit for the collaborative environment at Microsoft Research.
✨Tip Number 4
Prepare to discuss specific examples of how you've tackled complex problems using machine learning and distributed systems. Being able to articulate your thought process and the impact of your work will set you apart from other candidates.
We think you need these skills to ace Research Software Development Engineer, MSR AI for Science
Some tips for your application 🫡
Understand the Role: Before applying, make sure to thoroughly read the job description for the Research Software Development Engineer position. Understand the key responsibilities and required qualifications, especially in machine learning and distributed systems.
Tailor Your CV: Customise your CV to highlight relevant experience in machine learning, large datasets, and any work with open-source frameworks like PyTorch. Emphasise your problem-solving skills and any collaborative projects you've been involved in.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for scientific discovery and how your background aligns with the goals of the AI for Science team. Mention specific projects or experiences that demonstrate your expertise in the required areas.
Highlight Collaboration Experience: Since the role emphasises teamwork, include examples of past collaborations with cross-functional teams. Discuss how you contributed to achieving common goals and how you communicated effectively with team members from different disciplines.
How to prepare for a job interview at JobLeads GmbH
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning frameworks like PyTorch and your familiarity with distributed systems. Highlight specific projects where you've implemented these technologies, as this will demonstrate your hands-on expertise.
✨Emphasise Collaboration
Since the role involves working with cross-functional teams, share examples of how you've successfully collaborated with scientists or engineers in the past. This will show that you understand the importance of teamwork in achieving complex goals.
✨Demonstrate Problem-Solving Abilities
Prepare to discuss challenges you've faced in previous projects and how you overcame them. This could involve optimising data processing pipelines or troubleshooting issues with large datasets, showcasing your analytical skills.
✨Express Your Passion for Science
Convey your enthusiasm for pushing the boundaries of scientific discovery through AI. Share any relevant experiences or projects that reflect your commitment to using technology for real-world impact, particularly in areas like climate change or drug discovery.