Machine Learning Engineer

Responsibilities:

Model Development & Utilisation: Design, build, and train bespoke ML models, and identify, tune, and deploy third-party ML models (proprietary and open-source).

Production Deployment & MLOps: Manage the deployment of ML models into production environments, ensuring scalability and reliability, and build/maintain robust MLOps pipelines for CI/CD, monitoring, and automated retraining.

Data Pipeline Construction: Collaborate with data engineers/stewards to build and optimize data pipelines that feed ML models, ensuring data quality and efficient processing.

Cross-Functional Collaboration: Work closely with data scientists, product managers, and software engineers to define requirements, integrate models, and deliver impactful features.

Code Quality & Performance Tuning: Write clean, maintainable, and well-tested production-grade code, upholding high software engineering standards, and monitor/analyze model performance for optimization.
 

What You Need to Succeed (minimum qualifications):

Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related quantitative field.

Proven hands-on experience deploying machine learning models into a production environment.

Advanced proficiency in Python with deep experience in core ML/data science libraries, coupled with a strong foundation in software engineering principles.
 

What will give you a competitive edge (preferred qualifications):

Experience with MLOps tools and frameworks and containerisation technologies (Docker, Kubernetes).

Practical experience with Public Cloud (Microsoft Azure and Google Cloud Platform) and their ML services (, Azure ML, Vertex AI).

Proven experience with relevant DevSecOps concepts and tooling, including CI/CD, Git SCM, Containerisation, and Infrastructure-as-Code (HashiCorp Terraform).

Solid understanding of the theoretical foundations of machine learning algorithms, including deep learning, NLP, and classical ML.

Broad understanding of life science business models, regulatory requirements, and excellent communication skills to articulate complex technical decisions.
 

Additional Information:

Travel: 0-10%

Location: Hook, UK - Hybrid Work Environment