At a Glance
- Tasks: Develop scalable ML systems and models that impact millions globally.
- Company: Join Meta, a leader in tech innovation and connectivity.
- Benefits: Competitive salary, research opportunities, and a chance to work on groundbreaking projects.
- Other info: Collaborative environment with opportunities for professional growth and innovation.
- Why this job: Be at the forefront of machine learning and shape the future of technology.
- Qualifications: PhD in Machine Learning or related field; coding experience in Java, C++, or Python.
The predicted salary is between 60000 - 80000 £ per year.
In order to meet the demands of our scale, we approach machine learning challenges from a system engineering standpoint, both pushing the boundaries of scalable computing and tying together numerous complex platforms to build models that leverage trillions of actions, as well as building the best models under HW constraints. Our research and production implementations leverage many of the innovations being generated from Meta’s research in Distributed Computing, Artificial Intelligence, and Databases, and run on the same hardware and network specifications that are being open sourced through the Open Compute project. As a Research Scientist, you will help build machine learning systems and models behind Meta’s products, create web applications that reach millions of people, build high volume servers and be a part of a team that’s working to help connect people around the globe.
Responsibilities
- Develop highly scalable classifiers and tools leveraging machine learning, regression, and rules-based models with a high degree of autonomy.
- Suggest, collect and synthesize requirements and create effective feature roadmap.
- Build strong cross-functional partnerships and code deliverables in tandem with the engineering team.
- Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
- Actively seek and give feedback in alignment with Meta’s Performance Philosophy.
Minimum Qualifications
- Currently has, or is in the process of obtaining a PhD degree or completing a postdoctoral assignment in the field of Machine Learning, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
- Research and/or work experience in machine learning, deep learning, reinforcement learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, information retrieval or computer vision.
- Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Experience in systems software or algorithms.
- Experience in at least one of the following: Java, C/C++, Perl, PHP, or Python.
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or used contributions in open source repositories (e.g. GitHub).
Preferred Qualifications
- Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences such as ICML, NIPS, KDD or similar.
- Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
- Experience with Hadoop/Hbase/Pig or Mapreduce/Swazall/Bigtable.
- Experience working with ML Frameworks such as PyTorch, Spark ML or Tensorflow.
- Experience working and communicating cross-functionally in a team environment.
Research Scientist, Scalable ML Systems in London employer: Meta Platforms, Inc.
Meta is an exceptional employer for Research Scientists in Scalable ML Systems, offering a dynamic work culture that fosters innovation and collaboration. With access to cutting-edge technology and the opportunity to work on impactful projects that connect millions globally, employees benefit from a strong emphasis on professional growth and development. The company's commitment to open-source initiatives and its focus on scalable computing create a unique environment where creativity and technical expertise thrive.
StudySmarter Expert Advice🤫
We think this is how you could land Research Scientist, Scalable ML Systems in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to scalable ML systems. This is your chance to demonstrate your expertise and make a lasting impression.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past experiences in detail—this is where we can really shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Research Scientist, Scalable ML Systems in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in machine learning and scalable systems. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or research!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how you can contribute to our team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects:If you've worked on any cool projects, especially those involving ML frameworks like PyTorch or TensorFlow, make sure to mention them. We’re keen to see your hands-on experience and how you’ve tackled real-world problems.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Meta Platforms, Inc.
✨Know Your Stuff
Make sure you brush up on your machine learning concepts, especially those related to scalable systems. Be ready to discuss your research and any relevant projects in detail, as well as how they tie into the responsibilities of the role.
✨Showcase Your Collaboration Skills
Since this role involves building strong cross-functional partnerships, be prepared to share examples of how you've successfully worked with engineering teams or other departments in the past. Highlight your communication skills and how you adapt to different team dynamics.
✨Prepare for Technical Questions
Expect to face some technical challenges during the interview. Brush up on your coding skills in languages like Python or Java, and be ready to solve problems on the spot. Practising with coding challenges can help you feel more confident.
✨Align with Meta’s Performance Philosophy
Familiarise yourself with Meta’s approach to feedback and performance. Be ready to discuss how you seek and give constructive feedback in your previous roles, and how that aligns with their values. This shows you're a good cultural fit!
