Machine Learning Engineer (UK)

TN United Kingdom; London; On-site; GBP 40,000 - 80,000; Full time

Job summary

An innovative startup is on the lookout for a talented Machine Learning Engineer to join their dynamic team. This role offers the chance to work with cutting-edge AI technology, fine-tuning and optimizing models for real-world applications in video security. You will collaborate with industry experts and tackle exciting challenges at the intersection of user experience and machine learning. If you're passionate about developing production-grade software and eager to contribute to a fast-paced environment, this opportunity is perfect for you. Join a forward-thinking company that values excellence and creativity, and help shape the future of AI-driven solutions.

Benefits

Company equity % in an early-stage startup

Qualifications

• Strong fundamentals in machine learning and software engineering.
• Experience in productionizing models and optimizing performance.

Responsibilities

• Fine-tune and productionize open-source Pytorch models.
• Design experiments to evaluate trade-offs in latency and accuracy.
• Integrate models with downstream use cases and maintain existing ML applications.

Skills

Machine Learning Fundamentals

Production-grade Software Development

Deep Learning Research

C++ Programming

Docker and Containerization

Pytorch

Python3

Linear Algebra

Probability and Statistics

Tools

Pytorch

Docker

C++

ONNX Runtime

TensorRT

Job description

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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 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 trade-offs 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

• Company equity % in an early-stage startup.