- Be part of a groundbreaking team setting up and managing large scale compute clusters on AWS.
- Support multiple deep tech ML teams on extensive model training across hundreds of GPUs.
- Streamline the process adopt the right tools and super-charge the ML development process.
What You’ll Be Doing
As an ML Platform Engineer you’ll be integral in establishing the company’s compute cluster on AWS supporting deep tech ML teams on large scale model training and ensuring maximum utility and efficiency of the system.
You’ll also play a pivotal role in establishing best practices for running ML Models on distributed hardware and optimising the solution for ease-of-use.
This role puts you at the heart of the machine learning operation of a fast-paced innovative company using a mix of MLOps and DevOps.
What You’ll Need To Apply
- 3 years experience in Cloud Engineering MLOps or DevOps.
- Proficiency in setting up distributed compute in a cloud environment (AWS or other providers).
- Experience with Streaming/Batch Data Pipelines (Airflow Apache Beam Spark etc.).
- Familiarity with Event-driven systems and running Distributed processing in ML.
- Skills in Model deployment and serving (Docker – K8s/Terraform/Kubernetes).
What You’ll Get For Your Experience
You will enjoy competitive compensation (salary stock options bonus) with a base salary ranging between £80000 – £100000 depending on experience.
Additionally you will benefit from a highly collaborative researched-focused hybrid work environment in the London office (2-3 days p/week) 25 days of annual leave plus public holidays an inclusive company culture with regular socials and retreats) and excellent potential for career growth.
Please apply with an up-to-date CV and I will be in touch.