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.
Design and implement production machine-learning, generative-AI and justified agent-based services, including inference, feature processing, serving and integration.
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.
From the employer’s posting
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.
What you’ll do
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.
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.
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.
Qualification wording
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.
About Vodafone Group
VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value for customers by delivering intelligent solutions through Talent, Technology & Transformation.
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Python
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Where the posting names them
- 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.
- Production AI evaluation covering hallucination, bias, safety, robustness, quality and task performance.
- Cloud-based ML and AI engineering using Google Cloud Platform, Vertex AI or equivalent technologies.
- Model and AI-service observability across drift, latency, availability and cost.
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
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About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value for customers by delivering intelligent solutions through Talent, Technology & Transformation.
As the largest shared services organisation in the global telco industry with 30,000 FTE, our portfolio of next-generation solutions and services are designed in partnership with customers across Vodafone Group, local markets, and partner markets to simplify and drive growth. With our strategic partner Accenture, we work alongside our Vodafone customers, other Telco and tech companies to drive transformation, meet the challenges of our industry and ensure we stay relevant and resilient. This partnership is a unique, industry-first model which brings together the best of in-house and 3rd party capability.
We work with customers across 28 countries from 10 VOIS locations: Albania, Egypt, Hungary, India, Romania, Spain, Turkey, UK, Germany, Ireland, and with a network of teams in Czech Republic, Italy, Greece, and Portugal.
#VOIS #BeUnrivalled #CreateTheFuture
About this role
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.
This role will establish and apply MLOps and LLMOps practices across production AI solutions, using approved Data Platform capabilities. You will help ensure ML and generative-AI services meet appropriate standards for quality, safety, security, privacy, reliability, traceability and cost efficiency.
What you’ll do
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.
Who you are
You are an experienced ML, AI, software or platform engineer with substantial practical experience of taking machine-learning or AI solutions into production.
You will bring:
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.
Not a perfect fit?
Concerned you may not meet every requirement? Vodafone is committed to creating an inclusive workplace where everyone can thrive. If you are excited about this role but your experience does not align exactly with every aspect of the job description, you are encouraged to apply. You may be the right candidate for this or another opportunity, and the recruitment team will support you in exploring where your skills fit best.
What's in it for you
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.
What skills you will learn
Through this role, you will have opportunities to further develop your capabilities in:
Production engineering for machine-learning and generative-AI systems.
MLOps and LLMOps, including automated evaluation, model versioning, deployment, rollback and environment promotion.
Production AI evaluation covering hallucination, bias, safety, robustness, quality and task performance.
Cloud-based ML and AI engineering using Google Cloud Platform, Vertex AI or equivalent technologies.
Model and AI-service observability across drift, latency, availability and cost.
Engineering and operational controls for agent-based AI solutions.
Responsible AI engineering covering security, privacy, explainability, human oversight and model-risk controls.
Production incident response, runbook development, guardrails and audit evidence.
Technical assessment of build-versus-buy, portability and AI-provider trade-offs.
VOIS Equal Opportunity Employer Commitment
Vodafone recognises and celebrates the value of diversity in building a workforce that reflects the customers and communities it serves. No form of discrimination is tolerated. This includes, but is not limited to, discrimination based on race, colour, age, veteran status, gender identity, gender expression, sexual orientation, pregnancy, maternity or parental status, ethnicity, disability, religion or belief, political affiliation, trade union membership, nationality, citizenship, indigenous status, medical condition, HIV status, neurodiversity, social origin, cultural background, marital or civil partnership status, or socio-economic background.
Join Us
At Vodafone, we’re working hard to build a better future. A more connected, inclusive and sustainable world. As a dynamic global community, it's our human spirit, together with technology, that empowers us to achieve this.
We challenge and innovate in order to connect people, businesses, and communities across the world. Delighting our customers and earning their loyalty drive us, and we experiment, learn fast and get it done, together.
With us, you can be truly be yourself and belong, share inspiration, embrace new opportunities, thrive, and make a real difference.
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Location & working pattern
London, England, GB
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Work authorization
VOIS Equal Opportunity Employer Commitment
Vodafone recognises and celebrates the value of diversity in building a workforce that reflects the customers and communities it serves. No form of discrimination is tolerated. This includes, but is not limited to, discrimination based on race, colour, age, veteran status, gender identity, gender expression, sexual orientation, pregnancy, maternity or parental status, ethnicity, disability, religion or belief, political affiliation, trade union membership, nationality, citizenship, indigenous status, medical condition, HIV status, neurodiversity, social origin, cultural background, marital or civil partnership status, or socio-economic background.
Join Us