Machine Learning Engineer

Vertex Search; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

Vertex Search is partnering with a leading healthcare AI pioneer to recruit a Software / Machine Learning Engineer in central London. You will work at the intersection of software engineering and frontier ML research, building systems that enable breakthroughs in drug development and patient care.

In this role you will contribute to novel foundation models, optimize data pipelines and training loops, and collaborate with world-class researchers in a fast-moving startup environment.

Qualifications

• Strong general software engineering skills with clean, tested Python code.
• Experience handling large, messy datasets at scale.
• ML training and inference optimization for large data.
• Working knowledge of PyTorch and/or JAX training loops.
• Experience with HPC or multi-node GPU clusters (e.g. Slurm).
• Experience with health records, time-series or tabular data.
• Comfort across data pipelines, model training and evaluation.
• Experience in a startup or fast-moving research team; ships with minimal process.

Skills

Python

Data cleaning

Distributed training

PyTorch

JAX

HPC / Slurm

Time-series data

Tabular data

End-to-end systems

Tools

Slurm

Job description

We are working with a leading healthcare AI pioneer transforming drug development through cutting-edge artificial intelligence and world-leading multi-modal generative AI foundation models.

The Opportunity

We're seeking an exceptional Software / Machine Learning Engineer to join their central London office, working on novel Foundation Models. This is a rare opportunity to work at the intersection of advanced software engineering and frontier AI research, building systems that directly enable breakthroughs in drug development and patient care.

Your work will directly accelerate research velocity, enabling the team to iterate faster, experiment more effectively, and push the boundaries of what's possible in AI-driven healthcare.

Role Requirements

Core

• Strong general software engineering skills: clean, tested Python, comfortable owning systems end to end
• Hands-on experience with large, messy datasets - cleaning, joining, versioning, and validating data at scale
• Experience making ML training and inference run efficiently on very large data: caching, data loading, memory management, cross-node communication
• Working knowledge of PyTorch and/or JAX training loops
• Experience running workloads on HPC or multi-node GPU clusters (e.g. Slurm, distributed training)
• Prior work with health records, single-cell / cytometry data, or time-series
• Prior experience working with Tabular data / datasets
• Comfortable across the stack — data pipelines, model training, and evaluation — rather than specialising in one
• Experience in a startup or small, fast-moving research team; ships without heavy process

Nice to haves

• A biology or clinical background, or a demonstrated interest in learning the domain
• Familiarity with secure data environments (NHS TREs, data governance, de-identification)

Why This Role is Different

• Impact: Your work will directly accelerate research that's transforming drug development and saving lives. The tools you build will enable breakthroughs in understanding and treating complex diseases.
• Technical Challenge: Work on genuinely novel problems at the frontier of ML engineering. You'll tackle challenges around scale, complexity, and domain-specific constraints that few engineers ever encounter.
• Cutting-Edge Research: Collaborate daily with world-class researchers pushing the boundaries of AI in healthcare. You'll be exposed to the latest developments in foundation models, multi-modal learning, and medical AI.
• Autonomy & Ownership: Take ownership of critical systems and make architectural decisions that shape the technical direction. Your input will directly influence research capabilities and velocity.
• Fast-Paced Growth: Join during a period of rapid scaling with opportunities to grow your skills, take on increasing responsibility, and help shape the engineering culture.

This role is approx 4 days a week based in their London office, where the majority of the technical team, including ML researchers and engineering teams, are located. You'll be at the heart of R&D activities, with daily opportunities for face-to-face collaboration, whiteboard sessions, and rapid iteration with the team.

They foster a culture of intellectual curiosity, technical rigor, and collaborative problem-solving. The environment balances the urgency and pace of a fast-growing startup with the thoughtfulness and precision required for building foundation AI models that must meet the highest standards of accuracy and reliability.