AI & Machine Learning Engineer

DCV Technologies; Ringway; On-site; GBP 92,000 - 129,000; Full time

Job summary

DCV Technologies is seeking an experienced AI & Machine Learning Engineer on a contract basis to design, develop, and deploy scalable AI/ML solutions in a cloud-based environment. You will work with Python, PyTorch and GCP, building Generative AI apps with LLMs and RAG, and deploying via Docker, Vertex AI and KServe.

The role requires hands-on cloud engineering, MLOps, CI/CD, and experience with GPU workloads, experimentation, monitoring and performance optimization.

Qualifications

• Strong commercial experience in Python development and PyTorch (≤140 chars).
• Hands-on Google Cloud Platform (GCP) cloud engineering experience - essential (≤140 chars).
• Understanding of transformer architectures, LLMs, Generative AI and RAG (≤140 chars).
• Experience developing AI agents using frameworks or architectures such as ReAct (≤140 chars).
• Practical experience with Docker, cloud databases and containerised applications (≤140 chars).
• Knowledge of MLOps, CI/CD, model deployment, monitoring and production AI systems (≤140 chars).
• Experience with Vertex AI, KServe, GPU workloads and scalable cloud infrastructure (≤140 chars).
• Strong debugging, problem-solving and technical stakeholder communication skills (≤140 chars).

Responsibilities

• Design, develop, test and deploy AI/ML applications using Python, PyTorch and GCP.
• Build and integrate Generative AI solutions using transformer architectures, RAG and agent-based frameworks such as ReAct.
• Package, containerise and serve machine learning models using Docker, KServe and Vertex AI endpoints.
• Implement CI/CD pipelines, model registries, feature stores, model monitoring and drift detection.
• Optimise cloud infrastructure through GPU scheduling, autoscaling and cost-efficient model deployment.
• Support canary deployments, shadow deployments and A/B testing.
• Perform root cause analysis, troubleshoot technical issues and optimise application performance.
• Collaborate with engineering teams, project managers and stakeholders throughout the software development lifecycle.
• Produce technical documentation and support application integration and deployment.

Skills

Python

PyTorch

Google Cloud Platform (GCP)

LLMs

RAG

MLOps

Docker

CI/CD

Vertex AI

KServe

Tools

Docker

KServe

Vertex AI

Job description

AI & Machine Learning Engineer - Contract

Contract Type: Contract

Specialisms: Artificial Intelligence | Machine Learning | Generative AI | Google Cloud Platform (GCP)

We are recruiting an experienced AI & Machine Learning Engineer for an exciting contract opportunity focused on developing, deploying and optimising scalable AI and machine learning solutions within a cloud-based environment.

This role requires strong hands-on expertise in Python, PyTorch, Google Cloud Platform (GCP), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and MLOps.

Key Responsibilities

• Design, develop, test and deploy AI/ML applications using Python, PyTorch and GCP.
• Build and integrate Generative AI solutions using transformer architectures, RAG and agent-based frameworks such as ReAct.
• Package, containerise and serve machine learning models using Docker, KServe and Vertex AI endpoints.
• Implement CI/CD pipelines, model registries, feature stores, model monitoring and drift detection.
• Optimise cloud infrastructure through GPU scheduling, autoscaling and cost-efficient model deployment.
• Support canary deployments, shadow deployments and A/B testing.
• Perform root cause analysis, troubleshoot technical issues and optimise application performance.
• Collaborate with engineering teams, project managers and stakeholders throughout the software development lifecycle.
• Produce technical documentation and support application integration and deployment.

Essential Skills & Experience

• Strong commercial experience in Python development and PyTorch.
• Hands-on Google Cloud Platform (GCP) cloud engineering experience - essential.
• Understanding of transformer architectures, LLMs, Generative AI and RAG.
• Experience developing AI agents using frameworks or architectures such as ReAct.
• Practical experience with Docker, cloud databases and containerised applications.
• Knowledge of MLOps, CI/CD, model deployment, monitoring and production AI systems.
• Experience with Vertex AI, KServe, GPU workloads and scalable cloud infrastructure.
• Strong debugging, problem-solving and technical stakeholder communication skills.