MLOps Engineer

AI & MLOps Engineer

UK Remote | Generative AI |  Cloud-Native ML Systems

 

We are working in partnership with a global, technology-driven insights organisation to hire an  AI & MLOps Engineer  to join a cutting-edge  Synthetic Data team.

 

This is a high-impact opportunity to work at the forefront of  generative AI and machine learning platforms, helping turn advanced research into scalable, production-grade systems used across a global business.

 

The Opportunity

You’ll join a multidisciplinary team building a next-generation platform focused on:

• Synthetic data generation at scale
• AI-powered  data augmentation tools
• “Digital twin” models powered by LLMs
• Privacy-first, enterprise-grade ML infrastructure

 

The team blends  data science, software engineering, and research, with strong links to leading academic institutions—ensuring the work is both  scientifically rigorous and commercially impactful.

 

The Role

As an AI & MLOps Engineer, you’ll play a critical role in  bridging research and production, ensuring complex models are deployed in a reliable, scalable and cost-efficient way.

Key responsibilities include:

• Productionising cutting-edge AI models  (LLMs, diffusion models, synthetic data generators)
• Designing and maintaining  scalable ML pipelines and workflows
• Building  fault-tolerant orchestration layers  for long-running, compute-heavy jobs
• Implementing  CI/CD pipelines for machine learning, including model testing and versioning
• Driving  observability and monitoring, including model performance, data drift, and system health
• Optimising  cloud infrastructure and compute usage  (GPU/CPU, caching, scaling strategies)
• Developing robust  data architectures and asynchronous processing systems

 

You’ll work closely with applied ML researchers, acting as the key link that ensures innovation is translated into  real-world, production-ready solutions.

 

Technology Environment

You’ll be working across a modern AI/ML stack including:

• Languages & Frameworks:  Python, PyTorch
• MLOps & Platforms:  Kubeflow, Vertex AI, Kubernetes, Docker
• Backend Systems:  FastAPI, async job queues (Celery/RabbitMQ)
• Data & Storage:  GCP, BigQuery, Parquet/Arrow, vector databases
• LLM Tooling:  RAG architectures, PEFT/LoRA fine-tuning

 

What We’re Looking For

MLOps & Engineering Expertise

• Strong experience building and managing  complex ML pipelines (DAGs)
• Proven ability to  deploy generative AI models into production
• Hands-on with  CI/CD for ML, model registries, and reproducibility

 

Data & Systems Engineering

• Experience designing  high-throughput data pipelines  across structured and unstructured data
• Strong understanding of  asynchronous systems and APIs
• Expertise in  data validation and schema enforcement

 

AI/ML Knowledge

• Solid Python and PyTorch skills
• Familiarity with  LLMs, diffusion models, or similar architectures
• Experience with  model monitoring, evaluation, and performance optimisation

 

Why Apply?

• Work on  cutting-edge generative AI use cases  with real-world impact
• Be part of a  high-performing, research-driven engineering team
• Shape how advanced ML systems are deployed at  global scale
• Gain exposure to complex challenges across  AI, data, and platform engineering

 

If you’re passionate about building robust ML systems and want to work at the bleeding edge of AI innovation, we’d love to hear from you.

 

? Apply now or get in touch for a confidential conversation.