AI/ML engineer in MLOps

VOIS; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

VOIS is seeking a Senior ML & AI Engineer to join its Digital Engineering, Digital & IT team in the UK, spanning Newbury and Paddington. You will own the engineering lifecycle for production ML/AI services, from deployment to observability, in collaboration with data science and data engineering teams.

The role emphasizes MLOps, LLMOps, safety, privacy, explainability, and cost-aware design, with opportunities to influence model serving architectures, tooling choices, and build-versus-buy

Qualifications

• Substantial practical experience in software, platform or ML Engineering.
• Strong Python and software-engineering capability across APIs, automated testing, containers and continuous delivery.
• Experience with Vertex AI or equivalent managed ML platforms and model-serving services.
• Practical experience implementing MLOps, including model registries, versioning, deployment, rollback and monitoring.
• Knowledge of responsible AI engineering, including privacy, security, human oversight, explainability, safety and model-risk controls.

Responsibilities

• Design and productionise production machine-learning, generative-AI and agent-based services, including inference, feature processing, serving and integration.
• Productionise validated ML/AI solutions using platform capabilities and establish robust CI/CD pipelines.
• Establish MLOps and LLMOps practices covering versioning, testing, automated evaluation, deployment, rollback and monitoring.
• Own production monitoring, guardrails, runbooks, incident response and audit evidence for production AI services.
• Collaborate with Data Scientists and Data Engineers to translate validated approaches into reliable production services.

Skills

Python

APIs

Containers

MLOps

LLMOps

Vertex AI

Security

Explainability

Observability

Tools

Vertex AI

Job description

Описание:

We are seeking a Senior ML & AI Engineer to join our Digital Engineering, Digital & IT team in the UK, with flexible working across Newbury and Paddington. Reporting to the Data Products & Insights Lead, you will turn validated Data Science, machine-learning and generative-AI solutions into secure, reliable and scalable production services. You will own the engineering lifecycle for model and agent deployment, evaluation, observability and operational control, working closely with the Lead Data Scientist and Data Engineers.

Задачи:

Design and implement production machine-learning, generative-AI and justified agent-based services, including inference, feature processing, serving and integration Productionise validated ML, generative-AI and agent-based solutions using approved Data Platform capabilities Establish MLOps and LLMOps practices covering versioning, testing, automated evaluation, continuous delivery, deployment, rollback and environment promotion Implement proportionate AI evaluation covering quality, safety, hallucination, bias, robustness and task performance Own production monitoring and operational readiness across drift, latency, availability and cost Establish appropriate guardrails, runbooks, incident-response processes and audit evidence for production AI services Partner with the Lead Data Scientist and Data Engineers to translate validated scientific approaches into reliable production services Evaluate build-versus-buy decisions and provider trade-offs, considering performance, security, portability, reliability, provider dependency and cost Apply appropriate privacy, security, human oversight, explainability, safety and model-risk controls throughout the production lifecycle Use AI-assisted engineering practices while maintaining human accountability, validation, traceability and production discipline

Требования:

Substantial practical experience in software, platform or ML Engineering, including production ML/AI delivery Strong Python and software-engineering capability across APIs, automated testing, containers and continuous delivery Experience with Vertex AI or equivalent managed ML platforms and model-serving services Practical experience implementing MLOps, including model registries, versioning, deployment, rollback and monitoring Relevant experience with generative-AI evaluation and LLMOps Knowledge of responsible AI engineering, including privacy, security, human oversight, explainability, safety and model-risk controls Strong understanding of APIs, containers, cloud services and production observability An understanding of statistical and machine-learning concepts sufficient to identify and challenge invalid production assumptions Sound production judgement when balancing reliability, latency, scalability, portability, provider dependency and cost The ability to collaborate effectively with Data Scientists and Data Engineers to convert validated approaches into controlled production services

Условия:

The opportunity to engineer and productionise machine-learning, generative-AI and justified agent-based solutions across scalable digital services Ownership across the ML/AI production lifecycle, including deployment, evaluation, observability, operational readiness and control The opportunity to establish and mature MLOps and LLMOps delivery practices Practical experience applying responsible AI engineering across quality, safety, hallucination, bias, robustness, privacy and security The opportunity to influence technical decisions across model serving, tooling, provider selection and build-versus-buy choices Collaboration with Data Science and Data Engineering specialists on the transition from validated approaches to controlled production services Experience balancing real-world AI engineering considerations including reliability, latency, scalability, portability, provider dependency and cost Flexible UK working across Newbury and Paddington