MLOps Engineer

KDR Recruitment USA; United Kingdom; Remote; GBP 90,000 - 135,000; Full time

Job summary

KDR Recruitment USA is partnering with a technology-driven insights organisation to hire an AI & MLOps Engineer for UK remote work, focused on generative AI and cloud-native ML systems.

You will join a synthetic data team, bridging research and production, building scalable ML pipelines, deploying models, maintaining CI/CD, and optimizing cloud infrastructure across GPU/CPU. Collaboration with researchers and engineers is essential.

Qualifications

• 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.

Responsibilities

• 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.

Skills

ML pipelines

Deploying models to production

CI/CD for ML

Python

PyTorch

Tools

Kubeflow

Vertex AI

Kubernetes

Docker

FastAPI

Celery/RabbitMQ

GCP

Job description

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 anAI & MLOps Engineerto join a cutting-edgeSynthetic Data team.

This is a high-impact opportunity to work at the forefront ofgenerative 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-powereddata augmentation tools
• "Digital twin" models powered by LLMs
• Privacy-first, enterprise-grade ML infrastructure

The team blendsdata science, software engineering, and research, with strong links to leading academic institutions - ensuring the work is bothscientifically rigorous and commercially impactful.

The Role

As an AI & MLOps Engineer, you'll play a critical role inbridging 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 maintainingscalable ML pipelines and workflows
• Buildingfault-tolerant orchestration layersfor long-running, compute-heavy jobs
• ImplementingCI/CD pipelines for machine learning, including model testing and versioning
• Drivingobservability and monitoring, including model performance, data drift, and system health
• Optimisingcloud infrastructure and compute usage (GPU/CPU, caching, scaling strategies)
• Developing robustdata architectures and asynchronous processing systems

You'll work closely with applied ML researchers, acting as the key link that ensures innovation is translated intoreal-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 managingcomplex ML pipelines (DAGs)
• Proven ability todeploy generative AI models into production
• Hands-on withCI/CD for ML, model registries, and reproducibility

Data & Systems Engineering

• Experience designinghigh-throughput data pipelinesacross structured and unstructured data
• Strong understanding ofasynchronous systems and APIs
• Expertise indata validation and schema enforcement

AI/ML Knowledge

• Solid Python and PyTorch skills
• Familiarity withLLMs, diffusion models, or similar architectures
• Experience withmodel monitoring, evaluation, and performance optimisation

Why Apply?

• Work oncutting-edge generative AI use caseswith real-world impact
• Be part of ahigh-performing, research-driven engineering team
• Shape how advanced ML systems are deployed atglobal scale
• Gain exposure to complex challenges acrossAI, 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.