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- Tasks: Develop and benchmark cutting-edge ML algorithms on innovative hardware.
- Company: Join a pioneering deep-tech organisation at the forefront of machine learning.
- Benefits: Competitive salary, flexible work environment, and opportunities for research publication.
- Why this job: Make a real impact in ML by solving complex problems with advanced technology.
- Qualifications: Strong ML algorithm development experience and expertise in generative models required.
- Other info: Dynamic startup culture with a focus on growth and collaboration.
The predicted salary is between 36000 - 60000 ÂŁ per year.
If you want to push the boundaries of machine learning on cutting‑edge computing hardware, this role offers a rare chance to do exactly that. You’ll join a small, high‑impact team working at the forefront of next‑generation architectures, developing ML models and techniques that go beyond what’s possible on conventional systems. We are working exclusively with a pioneering deep‑tech organisation whose technology is used by leading global research institutions and industry innovators. Their multidisciplinary team is exploring new frontiers in generative modelling, hybrid neural network approaches, and advanced hardware‑accelerated ML.
As a Machine Learning Research Engineer, you’ll design and benchmark new algorithms, experiment with novel architectures, and contribute directly to the company’s software stack, research output, and technical roadmap. You’ll collaborate with internal experts, customers, and research partners to turn complex real‑world problems into high‑performance ML solutions.
Key Responsibilities- Develop and benchmark ML algorithms for novel computing hardware
- Work on generative models (flow, diffusion, GANs) and hybrid quantum‑classical architectures
- Translate customer and partner problems into hardware‑ready ML solutions
- Contribute new algorithms and examples to the user‑facing software stack
- Publish research and support IP protection activities
- Strong experience developing and benchmarking ML algorithms
- Expertise with generative models (flow, diffusion, and/or GANs)
- Experience with heterogeneous computing hardware (HPC, NPUs, ASICs, quantum, etc.)
- Excellent Python/PyTorch programming skills
- Master’s or PhD in a relevant field
- Multi‑GPU model experience
- Publication track record
- Customer‑facing experience
- Interest or knowledge in quantum computing
- Startup mentality: proactive, hands‑on, adaptable
- Strong communicator
- Curious, growth‑oriented, excited by emerging tech
We’re managing this role exclusively. If this sounds like your next challenge, apply now, and we’ll be in touch.
Machine Learning Research Engineer employer: IntaPeople
Contact Detail:
IntaPeople 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. 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 ML projects, especially those involving generative models or novel architectures. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and PyTorch skills. Practice coding challenges and be ready to discuss your past projects and how they relate to the role you're applying for.
✨Tip Number 4
Don’t just apply anywhere—apply through our website! We’re managing this role exclusively, so you’ll want to make sure your application stands out and gets into the right hands.
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 ML algorithms and generative models. We want to see how your skills align with the cutting-edge work we do, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about pushing the boundaries of machine learning and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any interesting ML projects, especially those involving novel architectures or hardware, make sure to mention them. We love seeing practical applications of your skills, so include links or descriptions of your work!
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 this exciting opportunity. Don’t miss out!
How to prepare for a job interview at IntaPeople
✨Know Your Algorithms
Make sure you brush up on the ML algorithms you've worked with, especially generative models like GANs and diffusion models. Be ready to discuss your experience in detail, including any challenges you faced and how you overcame them.
✨Showcase Your Hardware Knowledge
Since this role involves working with cutting-edge computing hardware, be prepared to talk about your experience with heterogeneous systems. Highlight any specific projects where you’ve benchmarked algorithms on HPC, NPUs, or even quantum systems.
✨Prepare for Technical Questions
Expect some deep technical questions during the interview. Practice explaining complex concepts clearly and concisely, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Demonstrate Your Curiosity
This role values a growth-oriented mindset. Be ready to discuss how you stay updated with emerging technologies and your interest in exploring new frontiers in machine learning. Share any recent research or projects that excite you!