ML Research Engineer (up to £120k + Equity)

Zettafleet; Greater London; On-site; GBP 75,000 - 120,000; Full time

Benefits offered by this job

Equity

Discretionary bonus

28 days + public holidays

Health insurance

Job summary

Zettafleet is hiring a Machine Learning Research Engineer to develop and enhance model training code and the underlying infrastructural software. You will work on pre-training, post-training and evaluation workloads to domain-adapt LLMs with customer data.

The role involves integrating training code with the backend, collaborating with forward-deployed engineers, and owning significant parts of the work with strong autonomy. Equity is offered.

Qualifications

• Experience in industry ML projects including data processing and distributed training.
• Understanding of LLM architectures, pre-training, post-training and evaluation.
• Proficient in Python with PyTorch; familiarity with TensorFlow/JAX is a plus.
• Experience deploying in cloud platforms and with containerisation (Docker).
• Strong CS fundamentals; ability to decompose complex problems into tasks.
• Excellent communication and teamwork skills.

Responsibilities

• Develop and enhance training recipes for large ML models.
• Integrate Python training code with the software infrastructure.
• Collaborate with forward-deployed engineers to capture customer needs.
• Work with autonomy and contribute to best practices and culture.

Skills

Python proficiency

Distributed training

LLMs understanding

Data processing

Problem solving

Collaboration

Tools

PyTorch

Docker

Cloud platforms (AWS/GCP/Azure)

Job description

Role: Machine Learning Research Engineer

Location: London (On-site; Liverpool Street)

Employment Type: Full-time and Permanent

Remuneration: £75k – £120k Base Salary + Discretionary Bonus + Equity

Zettafleet is an end-to-end platform for businesses and organisations to train their own LLM on their proprietary data. We can use non-conventional AI hardware and automatically source and combine GPUs (and other types of AI accelerators) from multiple cloud providers, enabling users to optimise for cost, duration or geographic location of the training.

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

We are looking for an experienced Machine Learning Research Engineer to develop and enhance our model training code and the underlying infrastructural software building blocks. You will work on pre-training, post-training and evaluation workloads, enabling our customers to easily domain-adapt LLM and embedding models with their data.

In this role, you will:

• Develop and enhance training recipes for large machine learning models.
• Work with the company’s backend team to integrate the Python training code with the underlying software infrastructure.
• Work closely with our forward-deployed engineers to understand model training requirements for the customers.
• Be given a high degree of autonomy and ownership over your work.
• Work closely with the founding team and contribute towards best practices, standards, and culture of the company.

What we are looking for:

• Research engineering: 2-3 years of industry experience in complex machine learning projects including data processing and training models in a distributed environment.
• LLMs: Understanding of LLM architectures, pre-training and/or post-training and evaluations.
• Programming languages: Excellent proficiency in Python using PyTorch (or a similar framework such as TensorFlow or JAX).
• Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker).
• 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. You have the ability to break down complex problems into actionable tasks.
• Collaboration and communication: Excellent interpersonal and communication skills with a desire to learn.

We would like to 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:

• Publications: At top-tier conferences, such as NeurIPS, ICML, ICLR or MLSys.
• Open-source: Contributions to and experience in open-source projects.
• Startup experience: Experience with a startup work environment and wider ecosystem.
• Work in an environment conducting cutting-edge research in AI.
• Competitive salary, equity and benefits package.
• 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.