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- Tasks: Develop and benchmark cutting-edge machine learning algorithms using quantum computing.
- Company: Join ORCA, a leader in quantum technology and machine learning innovation.
- Benefits: Enjoy a competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on scientific leadership and innovation.
- Why this job: Make a real impact in the future of technology with groundbreaking projects.
- Qualifications: Master's or PhD in relevant fields and expertise in ML algorithms required.
The predicted salary is between 36000 - 60000 £ per year.
Location: Central London, Hybrid
Employment Type: Full Time
Role Overview
As Machine Learning Engineer, you will be advancing the state of the art in machine learning using novel computing hardware. You will be responsible for developing and benchmarking new algorithms and applications that leverage the unique capabilities of ORCA's quantum processors. Combining your knowledge of ML algorithms with computing hardware, applied use-cases and trends in machine learning, you will extend ORCA's competitive capabilities with our customers and in the marketplace.
Key Responsibilities
- Develop and benchmark new machine learning algorithms that use ORCA's quantum computer. Your focus will be on generative models (flow models, diffusion and GANs) and novel hybrid quantum-classical neural network architectures.
- In collaboration with clients and partners, map relevant problems to ORCA's hardware and deliver projects demonstrating how ORCA's technology can solve these problems.
- Contribute to ORCA's user-facing software stack by adding new algorithms, applications and examples.
- Contribute to ORCA's scientific leadership by publishing results and working with the legal team to protect the IP associated with your work.
Required qualifications, skills and experience
- Expertise developing and benchmarking machine learning algorithms.
- Experience with flow models, diffusion and/or GANs.
- Excellent ML-oriented programming skills (Pytorch, Python, git).
- Master's or PhD in a relevant field (physics, computer science, etc.).
Preferred technical skills and experience
- Experience with heterogeneous computing hardware (HPC, NPUs, ASICs, quantum, etc.).
- Experience working with multi-GPU models.
- A publication track record in ML.
- Experience working in front of and with customers.
- Knowledge of quantum computing.
Additional requirements
- Ability to work both autonomously and collaboratively.
- Excellent communication skills – particularly in a commercial setting.
- Growth mindset, result-driven.
- Enthusiasm about new technologies.
- Previous commercial experience required.
If you're interested in this job opportunity at ORCA, please email us at careers@orcacomputing.com. Ensure the subject line clearly states the role you are applying for or inquiring about, and kindly attach your CV.
Machine Learning Research Engineer in London employer: ORCA Computing Ltd
Contact Detail:
ORCA Computing Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Research Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. We can’t stress enough how important it is to build relationships that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those involving generative models or quantum computing. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We recommend practicing common ML interview questions and coding challenges to boost your confidence and impress your interviewers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Machine Learning Research Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Research Engineer role. Highlight your experience with ML algorithms, especially generative models like flow models and GANs. We want to see how your skills align with what we're looking for!
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 quantum computing. Share specific examples of your work that demonstrate your expertise and enthusiasm – we love a good story!
Showcase Your Projects: If you've worked on any relevant projects, make sure to mention them in your application. Whether it's a publication or a personal project, we want to see how you've applied your skills in real-world scenarios. It helps us understand your hands-on experience!
Follow Application Instructions: When applying, be sure to follow our instructions carefully. Email your application to the provided address and include the job title in the subject line. This shows us that you pay attention to detail, which is super important in our field!
How to prepare for a job interview at ORCA Computing Ltd
✨Know Your Algorithms
Make sure you brush up on the latest machine learning algorithms, especially generative models like flow models, diffusion, and GANs. Be ready to discuss your experience with these and how they can be applied to ORCA's quantum processors.
✨Showcase Your Programming Skills
Prepare to demonstrate your programming prowess in Pytorch and Python. You might be asked to solve a coding challenge or explain your previous projects, so have examples ready that highlight your ML-oriented programming skills.
✨Understand Quantum Computing Basics
Even if you're not a quantum computing expert, having a solid understanding of its principles will set you apart. Familiarise yourself with how quantum hardware differs from classical systems and think about how this could impact machine learning applications.
✨Communicate Effectively
Since this role involves collaboration with clients and partners, practice articulating complex concepts in simple terms. Prepare to discuss how you've successfully communicated technical information in previous roles, as strong communication skills are key.