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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: 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: Be at the forefront of technology, solving real-world problems with quantum computing.
- Qualifications: Expertise in ML algorithms and programming skills in Pytorch and Python.
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 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
✨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 valuable personal connections can be in landing that dream job.
✨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 even doing mock interviews with friends or mentors to build confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining our team at ORCA.
We think you need these skills to ace Machine Learning Research Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning algorithms, especially flow models, diffusion, and GANs. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about working with ORCA’s quantum processors and how your background makes you a perfect fit for the Machine Learning Research Engineer role. Let your passion show!
Showcase Your Projects: If you've worked on any cool projects involving ML algorithms or quantum computing, make sure to mention them. We love seeing practical applications of your skills, so include links or descriptions of your work that demonstrate your expertise.
Follow Application Instructions: When applying, remember to email us at careers@orcacomputing.com with the correct subject line and attach your CV. Following these simple steps shows us you can pay attention to detail, which is super important in this role!
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 how you've developed or benchmarked these in the past, as this will show your expertise and passion for the field.
✨Showcase Your Programming Skills
Since excellent ML-oriented programming skills are a must, be prepared to talk about your experience with Pytorch, Python, and git. You might even want to bring examples of your code or projects to demonstrate your capabilities during the interview.
✨Understand Quantum Computing
Given the focus on ORCA’s quantum processors, it’s crucial to have a solid understanding of quantum computing principles. Familiarise yourself with how quantum technology can enhance machine learning applications, and be ready to discuss any relevant experience you have.
✨Communicate Effectively
Strong communication skills are key, especially in a commercial setting. Practice explaining complex concepts in simple terms, as you may need to convey technical details to clients or partners. This will highlight your ability to work collaboratively and autonomously.