At a Glance
- Tasks: Lead innovative deep learning projects to combat climate change and enhance model performance.
- Company: Join a forward-thinking startup focused on sustainability and cutting-edge technology.
- Benefits: Flexible working arrangements, competitive salary, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on innovation and sustainability.
- Why this job: Make a real impact on the environment while pushing the boundaries of deep learning.
- Qualifications: 3+ years in deep learning, proficient in Python and PyTorch, with strong analytical skills.
The predicted salary is between 60000 - 80000 € per year.
If you are motivated by the challenge of applying cutting-edge Deep Learning in messy, real-world environments where your input directly reduces the global carbon footprint, you are in the right place.
- 3+ years (5+ preferred) applying deep learning in industry settings
- Experience with applying latest Deep Learning research in PyTorch
- Experience with active learning, semi-supervised learning, learning from noisy labels, model robustness (at least two)
- Experience with architectures such as YOLO, ViT, ResNet
- Ability to write clear, efficient, and scalable code using Python and PyTorch
- Experience with numpy, scipy, OpenCV, Albumentations
- Analytical detail-oriented mindset with strong abstract thinking and a solid theoretical understanding of neural networks
- (Desirable) Experience in the waste industry
- (Desirable) Startup or scale up experience
You will report directly to the Head of Deep Learning. You will work within a focused DL team and collaborate with a dedicated Data team. You will also regularly interact with the wider company to ensure technical alignment across the organisation.
If you live in London or within commuting distance, we’d like you to come into the office at least once a week. If you’re elsewhere in the UK, we ask you to come in once a month, and for our Quarterly All Hands.
As a Senior Deep Learning Research Engineer, you are an architect of a sustainable future. You will have the autonomy to propose, discuss, and implement the best solutions for our customers.
Pushing the boundaries of deep learning by building upon the latest research in object detection and classification. Developing deep learning methods using best software development practices; training, analyzing, and reporting model performance. Developing internal tools to further automate research and analysis workflows.
Senior Deep Learning Research Engineer employer: Deepstreamtech
Join a forward-thinking company that is at the forefront of applying deep learning to tackle real-world challenges, particularly in reducing the global carbon footprint. With a collaborative work culture and a commitment to employee growth, you will have the opportunity to innovate alongside a dedicated team while enjoying flexible working arrangements. Located in London, this role offers the unique advantage of being part of a mission-driven organisation that values your contributions and encourages professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Deep Learning Research Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow deep learning enthusiasts. 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 involving PyTorch and deep learning architectures like YOLO or ResNet. 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 theoretical knowledge and practical applications of deep learning. Be ready to discuss your experience with active learning and model robustness, as these are hot topics in the field right now.
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Deep Learning Research Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with deep learning and the specific technologies mentioned in the job description. We want to see how your skills align with our needs, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about deep learning and how you can contribute to reducing the global carbon footprint. We love seeing genuine enthusiasm for the role and our mission.
Showcase Your Projects:If you’ve worked on any interesting deep learning projects, make sure to mention them! Whether it’s a personal project or something from your previous job, we want to see your hands-on experience and creativity in action.
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 gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at Deepstreamtech
✨Know Your Deep Learning Stuff
Make sure you brush up on the latest deep learning research, especially in areas like object detection and classification. Be ready to discuss your experience with architectures like YOLO, ViT, and ResNet, as well as any projects where you've applied these in real-world settings.
✨Show Off Your Coding Skills
Since you'll be writing clear and efficient code in Python and PyTorch, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges that involve numpy, scipy, and OpenCV to showcase your skills.
✨Talk About Your Experience
Highlight your experience with active learning, semi-supervised learning, and model robustness. Be specific about how you've tackled challenges in these areas and how your contributions have made a difference in previous roles, especially if you have experience in the waste industry.
✨Be Ready to Collaborate
As you'll be working closely with both the Deep Learning team and the Data team, emphasise your teamwork skills. Share examples of how you've successfully collaborated in the past, and be prepared to discuss how you would ensure technical alignment across the organisation.
