Senior Machine Learning Engineer

Dimensionalconsultingltd; Manchester; On-site; GBP 70,000 - 90,000; Full time

Benefits offered by this job

Competitive salary with annual performance bonus

£2,000 annual conference and learning budget

Private healthcare and dental cover

Hybrid working — flexible office/remote split

30 days annual leave plus bank holidays

Stock option scheme and pension matching

Latest hardware access

Job summary

Dimensionalconsultingltd is seeking a Senior Machine Learning Engineer to lead the design, development, and deployment of production-grade machine learning systems for global clients. You will work at the intersection of research and engineering.

Ideal candidates will have a strong background in Python, ML frameworks, and cloud services. The role offers a competitive salary, hybrid work arrangements, and ample annual leave.

Qualifications

• 5+ years of experience in machine learning engineering or applied ML research.
• Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics.
• Experience deploying ML models at scale using Docker, Kubernetes, or serverless.

Responsibilities

• Design and implement end-to-end ML pipelines from experimentation to production.
• Lead model development across NLP, computer vision, and time-series forecasting.
• Mentor junior ML engineers and conduct technical code reviews.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

Docker

Kubernetes

Cloud ML services

MLOps tools

Education

MSc or PhD in Computer Science or related field

Tools

MLflow

Weights & Biases

DVC

Job description

Design, train, and deploy production-grade ML models.

About the Role

As a Senior Machine Learning Engineer, you will lead the design, development, and deployment of production-grade machine learning systems for global enterprise clients. You'll work at the intersection of research and engineering, translating cutting‑edge papers into scalable, reliable solutions. This is a high‑impact role where you'll mentor junior engineers, shape our ML architecture, and collaborate directly with clients to solve their most complex challenges.

• Design and implement end-to-end ML pipelines from experimentation to production
• Lead model development across NLP, computer vision, and time‑series forecasting
• Architect scalable model serving infrastructure on cloud platforms (AWS/GCP/Azure)
• Conduct rigorous model evaluation, A/B testing, and performance monitoring
• Mentor junior ML engineers and conduct technical code reviews
• Collaborate with data engineers to optimise feature stores and data pipelines
• Stay current with latest ML research and evaluate applicability to client projects

Requirements

• 5+ years of experience in machine learning engineering or applied ML research
• Strong proficiency in Python, PyTorch or TensorFlow, and Scikit-learn
• Experience deploying ML models at scale using Docker, Kubernetes, or serverless
• Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics
• Experience with cloud ML services (SageMaker, Vertex AI, or Azure ML)
• Strong software engineering practices: version control, testing, CI/CD
• MSc or PhD in Computer Science, Machine Learning, or related field

Nice to Have

• Published research in top ML venues (NeurIPS, ICML, ACL, CVPR).
• Experience with MLOps tools: MLflow, Weights & Biases, DVC.
• Familiarity with distributed training frameworks (DeepSpeed, Horovod).
• Experience with LLM fine-tuning and prompt engineering.
• Contributions to open-source ML projects.

• Competitive salary with annual performance bonus.
• £2,000 annual conference and learning budget.
• Private healthcare and dental cover.
• Hybrid working — flexible office/remote split.
• 30 days annual leave plus bank holidays.
• Stock option scheme and pension matching.
• Latest hardware (M-series MacBook Pro, GPU workstation access).

About the Team

Our AI Research team is a tight‑knit group of 8 researchers and engineers passionate about pushing the boundaries of applied AI. We publish at top venues, contribute to open-source, and work on problems spanning healthcare diagnostics, financial risk modelling, and autonomous systems. You'll have the freedom to explore new ideas while delivering real value to clients.