Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join us as a Machine Learning Engineer to optimise AI video systems and enhance user experience.
- Company: Coram.AI is revolutionising the video security industry with cutting-edge AI technology.
- Benefits: Enjoy company equity, a dynamic startup environment, and opportunities for rapid personal growth.
- Why this job: Work on exciting challenges at the forefront of AI and video technology in a supportive team.
- Qualifications: Strong software engineering skills and a solid foundation in machine learning principles are essential.
- Other info: Ideal for those passionate about deep learning and eager to make an impact in a fast-paced setting.
The predicted salary is between 43200 - 72000 £ per year.
Started in 2021, Coram.AI is building the best business AI video system on the market. Powered by the next-generation video artificial intelligence, we deliver unprecedented insights and 10x better user experience than the incumbents of the vast but stagnant video security industry. Our customers range from warehouses, schools, hospitals, hotels, and many more, and we are growing rapidly. We are looking for someone to join our team to help us scale our systems to meet the user demand and to ship new features.
Founded by Ashesh (CEO) and Peter (CTO), we are serial entrepreneurs and experts in AI and robotics. Our engineering team is composed of industry experts with decades of research and experience from Lyft, Google, Zoox, Toyota, Facebook, Microsoft, Stanford, Oxford, and Cornell. Our go-to-market team consists of experienced leaders from Verkada. We are venture-backed by 8VC + Mosaic, revenue-generating, and have multiple years of runway.
Being part of our team means solving interesting problems at the intersection of user experience, machine learning and infrastructure. It also means committing to excellence, learning, and delivering great products to our customers in a high-velocity startup.
The role involves:
- Taking an existing open-source Pytorch model, fine-tuning, productionising them in C++ runtime, and optimising for latency and throughput.
- Fine-tuning an open-source model on our in-house data set as needed.
- Designing thoughtful experiments in evaluating the trade-offs between latency and accuracy on the end customer use case.
- Integrating the model with the downstream use case and fully owning the end metrics.
- Maintaining and improving all existing ML applications in the product.
- Reading research papers and developing ideas on how they could be applied to video security use cases, and converting those ideas to working code.
Requirements:
- You should be a good software engineer who enjoys writing production-grade software.
- Strong machine learning fundamentals (linear algebra, probability and statistics, supervised and self-supervised learning).
- Keeping up with the latest in deep learning research, reading research papers, and familiarity with the latest developments in foundation models and LLMs.
- (Good to have) Comfortable with productionising a Pytorch model developed in C++, profiling the model for latency, finding bottlenecks, and optimising them.
- Good understanding of docker and containerisation.
- (Good to have) Experience with Pytorch and Python3, and comfortable with C++.
- (Good to have) Understanding of Torch script, ONNX runtime, TensorRT.
- (Good to have) Understanding of half-precision inference and int8 quantisation.
What we offer:
- Company equity % in an early-stage startup.
Machine Learning Engineer (UK) (Basé à London) employer: Golden Bees
Contact Detail:
Golden Bees Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (UK) (Basé à London)
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning, particularly in video AI and deep learning. This will not only help you understand the company's products better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your hands-on experience with Pytorch and C++ by working on personal projects or contributing to open-source initiatives. This practical knowledge can set you apart from other candidates and demonstrate your ability to productionise models effectively.
✨Tip Number 3
Prepare to discuss specific examples of how you've optimised machine learning models for latency and throughput in previous roles or projects. Being able to articulate your problem-solving process will impress the interviewers.
✨Tip Number 4
Network with professionals in the AI and machine learning community, especially those who have experience in video security applications. Engaging with industry experts can provide valuable insights and potentially lead to referrals within the company.
We think you need these skills to ace Machine Learning Engineer (UK) (Basé à London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, software engineering, and any specific projects involving Pytorch or C++. Emphasise your understanding of deep learning fundamentals and any practical applications you've worked on.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific projects or experiences that align with Coram.AI's mission and the responsibilities of the Machine Learning Engineer position. Show how your skills can contribute to their goals.
Showcase Relevant Projects: If you have worked on any projects related to video security, machine learning, or optimising models, be sure to include these in your application. Provide links to your GitHub or portfolio where applicable, demonstrating your coding skills and problem-solving abilities.
Highlight Continuous Learning: Mention any recent courses, certifications, or research papers you've engaged with that are relevant to the latest developments in machine learning and AI. This shows your commitment to staying updated in a fast-evolving field.
How to prepare for a job interview at Golden Bees
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning frameworks, particularly Pytorch. Highlight any projects where you've fine-tuned models or worked with C++ to productionise them, as this is crucial for the role.
✨Demonstrate Problem-Solving Abilities
Expect to face technical challenges during the interview. Be ready to explain how you approach problem-solving, especially in terms of evaluating trade-offs between latency and accuracy in machine learning applications.
✨Stay Updated on Industry Trends
Familiarise yourself with the latest research in deep learning and video security. Mention any recent papers you've read and how their findings could be applied to the company's products, showing your passion for continuous learning.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's technology stack, team dynamics, and future projects. This not only shows your interest in the role but also helps you gauge if the company aligns with your career goals.
