Graduate Software Engineer – ML Data Platform

JR United Kingdom; London; On-site; GBP 60,000 - 70,000; Full time

Job summary

A stealth-mode AI laboratory in London is seeking a Graduate Software Engineer for their ML Data Platform. The role involves designing scalable data solutions and collaborating with a talented team. Ideal candidates will have strong back-end development skills, proficiency in Python, and a passion for data-driven problem solving. The position offers a competitive salary, equity, and opportunities for professional growth.

Benefits

Competitive salary

Equity

Financial assistance for relocation

28 days + public holidays allowance

Opportunities for professional growth

Qualifications

• Experience in back-end engineering developing data platforms or ETL pipelines.
• Proficiency in Python for data pipelines and micro-services.
• Strong analytical problem-solving skills.

Responsibilities

• Design and develop a highly-scalable data platform.
• Architect training data validation and integrity mechanisms.
• Work closely with the founding team on best practices.

Skills

Problem solving

Collaboration and communication

Tools

Python

AWS

GCP

Azure

Docker

Terraform

Job description

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Graduate Software Engineer – ML Data Platform, London

Location: London (Liverpool Street)

Employment Type: Full-time and Permanent

Remuneration: £60–70k Base Salary + Discretionary Bonus + Equity

We are a stealth-mode AI laboratory researching and developing Machine Learning models.

The founding team consists of Cambridge graduates and former engineers at Microsoft, Bloomberg, and Goldman Sachs. We are backed by prominent investors from the US and the UK, including institutional VC funds and C-level executives of global technology companies.

In this role, you will:

• Design and develop a highly-scalable data platform capable of ingesting and processing hundreds of terabytes of training data.
• Design and develop methodologies and metrics to better understand the underlying quality, structure, and distribution of training data.
• Architect training data validation, integrity, and safety mechanisms for state-of-the-art ML models.
• Work closely with the founding team and contribute towards best practices, standards, and culture of the company.

What we are looking for:

• Back-end development: Experience in back-end engineering developing data platforms or large-scale extract-transform-load (ETL) pipelines.
• Programming languages: Proficiency in Python for data pipelines, distributed systems, and micro-services.
• Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP, or Azure), understanding of containerisation (e.g., Docker), and infrastructure-as-code software (e.g., Terraform).
• Algorithms and data structures: Excellent understanding of core CS fundamentals, including common abstract data structures and algorithms, with the ability to apply them to optimise production systems.
• Problem solving: Strong analytical problem-solving skills and attention to detail. Ability to break down complex problems into actionable tasks.
• Collaboration and communication: Excellent interpersonal and communication skills with a desire to learn.

We acknowledge that almost no candidate checks every box – and that is perfectly fine. If you are passionate about data and enjoy solving complex challenges, we would love to hear from you.

Nice to have:

• Machine Learning: Experience in generative models, LLMs, multi-modal models, and Deep Learning more generally.
• Open-source: Contributions to and experience in open-source projects.
• Front-end: Experience with TypeScript and front-end libraries such as React or Next.js.
• Startup experience: Experience with a startup work environment and wider ecosystem.
• Work in an environment conducting cutting-edge research in AI.
• An official role title of “Founding Engineer” – make an impact on day one.
• Competitive salary, equity, and benefits package.
• Financial assistance for relocation to London.
• 28 days + public holidays allowance.
• Opportunities for professional growth and progression with your career.
• Work on challenging engineering problems that have a real impact on the industry.
• Work with high-profile customers and technology partners.