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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 a competitive salary, equity options, and comprehensive dental and vision insurance.
- Why this job: Be part of a dynamic startup, tackling exciting challenges in AI and machine learning.
- Qualifications: Strong software engineering skills and a solid foundation in machine learning principles required.
- Other info: Work alongside industry experts from top tech companies and contribute to innovative projects.
The predicted salary is between 64000 - 96000 £ per year.
Who We Are
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.
Team you will work with
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
We are hiring a Machine Learning engineer. Take an existing open-source Pytorch model, fine-tune, productionize them in C++ runtime, and optimize for latency and throughput. Take an open-source model and fine-tune them on our in-house data set as needed. Design thoughtful experiments in evaluating the tradeoffs between latency and accuracy on the end customer use case. Integrate the model with the downstream use case and fully own the end metrics. Maintain and improve all existing ML applications in the product. Read research papers and develop ideas on how they could be applied to video security use cases, and convert 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 productionizing a Pytorch model developed in C++, profiling the model for latency, finding bottlenecks, and optimizing them.
- Good understanding of docker and containerization.
- (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 quantization.
What We Offer
- £80-150k base.
- Company equity % in an early-stage startup.
- 100% company-paid private Dental & Vision insurance.
Contact Detail:
Coram AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (UK)
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning and deep learning, especially those related to video security. 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 experience 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 thought process and the results achieved will impress the interviewers.
✨Tip Number 4
Network with professionals in the AI and machine learning community, particularly those who have experience in video security. Engaging with industry experts can provide valuable insights and potentially lead to referrals within Coram.AI.
We think you need these skills to ace Machine Learning Engineer (UK)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly with Pytorch and C++. Emphasise any projects where you've fine-tuned models or worked on production-grade software.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific projects or experiences that align with their needs, such as your familiarity with deep learning research and productionising models.
Showcase Your Skills: Include a section in your application that showcases your technical skills. Highlight your understanding of linear algebra, probability, and statistics, as well as any experience with Docker and containerization.
Demonstrate Continuous Learning: Mention any recent research papers you've read or courses you've taken related to machine learning and AI. This shows your commitment to staying updated with the latest developments in the field.
How to prepare for a job interview at Coram AI
✨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 optimised them for performance, as this aligns closely with what the company is looking for.
✨Understand the Company’s Product
Familiarise yourself with Coram.AI's video AI system and its applications in various industries. Being able to discuss how your skills can contribute to enhancing their product will demonstrate your genuine interest in the role.
✨Prepare for Problem-Solving Questions
Expect to tackle questions that assess your problem-solving abilities, especially around trade-offs between latency and accuracy. Practising these types of scenarios will help you articulate your thought process during the interview.
✨Stay Updated on Industry Trends
Since the role involves keeping up with the latest in deep learning research, be ready to discuss recent advancements or papers that excite you. This shows your passion for the field and your commitment to continuous learning.
