Machine Learning Engineer - Scaling

BioTalent; Greater London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading technology firm in Greater London seeks a Machine Learning Engineer to develop and optimize advanced AI systems. You'll be responsible for building efficient pipelines and collaborating with cross-disciplinary teams. The ideal candidate will have an MSc or PhD in Machine Learning or a related field, strong programming skills in Python, and experience with MLOps. This role is perfect for someone eager to tackle challenging technical problems and innovate within a fast-paced environment.

Qualifications

• Advanced degree in Machine Learning, Computer Science, or related field required.
• Proficient in programming with Python and relevant libraries.
• Experience with machine learning pipelines for production.

Responsibilities

• Build scalable training and inference pipelines for AI models.
• Optimize model performance across operational environments.
• Collaborate with researchers to transition experimental code to production.

Skills

Python programming

Knowledge of PyTorch

Understanding of AI architectures

Experience with MLOps

Education

MSc or PhD in Machine Learning or related field

Tools

TensorFlow

Docker

Weights & Biases

Job description

Do you want to help transform an industry by applying cutting-edge technology to solve meaningful, real-world problems? Join an innovative, forward-thinking team building impactful solutions in a fast-paced and collaborative environment.

As a Machine Learning Engineer - Scaling, you’ll play a critical role in developing and optimising advanced machine learning systems to address complex challenges. You will work closely with cross-disciplinary teams to productionise model workflows, explore innovative methods, and contribute to scalable and efficient AI applications. This is an exciting opportunity for individuals who thrive on technical challenges, value ownership, and are motivated by innovation and impact

Responsibilities

• Build and maintain scalable training and inference pipelines for modern AI models (e.g. Transformers, Sequence Models, etc.).
• Optimise model performance, ensuring low latency and high throughput in various operational environments.
• Design and implement reusable, modular machine learning components for internal or broader use.
• Collaborate with researchers to transition experimental code into fully operational, production-grade systems.
• Manage and enhance machine learning infrastructure—including data pipelines, distributed computing, and experiment tracking tools.

Requirements

Essential Qualifications

• MSc or PhD in fields such as Machine Learning, Computer Science, Applied Mathematics, or closely related areas.
• Strong programming expertise in Python, with proficiency in libraries like PyTorch, JAX, or TensorFlow.
• Hands‑on experience developing and scaling machine learning pipelines for production environments.
• Familiarity with MLOps practices and tools such as Weights & Biases, Ray, or Docker.
• In-depth understanding of modern AI architectures, including Transformers, Diffusion Models, or similar frameworks.
• A proactive attitude, with the ability to thrive in a high‑speed environment and adapt to ambiguity.

Bonus Points

• Contributions to open‑source machine learning projects or tools.
• Experience in distributed training, model compression, or large‑scale model serving.
• Expertise in scaling AI systems for large post‑training workloads.
• Experience integrating machine learning systems into user‑facing applications or APIs.
• An interest in applying machine learning in fields like biology, healthcare, or other specialised domains (prior experience not required but advantageous).

What We’re Looking For

If you are excited by complex and deeply technical challenges, enjoy working in a collaborative and fast‑paced team environment, and want to make a real impact in a rapidly growing sector, this role is for you. We value innovation, ownership, and enthusiasm for tackling industry‑defining problems.