Machine Learning Engineer – Contract

AND Digital

. Help organisations navigate the future of technology by combining human expertise, emerging technology, and AI .

Posted 10/6/2026contractMilton Keynes • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in deploying and operating artificial intelligence and machine learning architectures, with a strong foundation in Python and SQL. Capable of constructing high-volume batch processing systems and real-time microservices while ensuring alignment with product outcomes and effective communication with stakeholders.

Highest-signal resume keywords

Artificial Intelligence ArchitectureMachine Learning LifecyclePython ProficiencyCloud TechnologiesDeployment Pipelines

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Artificial IntelligenceMachine LearningBatch Processing SystemsMicroservicesAutomated Continuous RetrainingSystem ObservabilityPythonSQLPyTorchTensorFlow

Soft Skills

CommunicationCollaborationInfluencingDetail-OrientedInquisitive

Tools & Technologies

Google Cloud PlatformBigQueryVertex AIDataflowDockerKubernetesVersion ControlGenerative AILarge Language ModelsAgent Orchestration Tools

Industry Keywords

Production EcosystemsTechnical Trade-OffsStakeholder EngagementMultidisciplinary TeamsModern Machine Learning Tooling

Tech Stack

Tools & technologies

BigQueryCloudDockerGoogle Cloud PlatformKubernetesMicroservicesPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Help organisations navigate the future of technology by combining human expertise, emerging technology, and AI
Deploy and operate artificial intelligence and machine learning architectures in production ecosystems
Construct high-volume batch processing systems and real-time microservices
Implement automated continuous retraining and system observability
Architect sustainable solutions across the full machine learning lifecycle
Align technical solutions with product outcomes
Collaborate with engineering peers, non-technical business partners, clients, and multidisciplinary teams
Communicate technical trade-offs and build trust with stakeholders

Requirements

What you’ll need

Hands-on experience deploying and operating artificial intelligence and machine learning architectures in production ecosystems
Proficiency in constructing high-volume batch processing systems, real-time microservices, automated continuous retraining, and system observability
Deep understanding of the entire machine learning lifecycle
Strong technical foundations in Python and SQL
Experience with PyTorch, TensorFlow, and Scikit-learn
Practical expertise with public cloud environments, preferably Google Cloud Platform technologies such as BigQuery, Vertex AI, and Dataflow
Experience with deployment pipelines, version control, Docker, and Kubernetes
Familiarity with generative AI, Large Language Models, and agent orchestration tools such as ADK, LangChain, or AutoGen
Ability to articulate technical trade-offs and influence engineering peers and non-technical business partners
Inquisitive, self-starting, detail-oriented approach and willingness to explore modern machine learning tooling

Benefits

Comp & perks

Equal opportunities and diversity and inclusion commitment
Support and adjustments for the application or interview process
Contract employment arrangement