What AI & Emerging Technologies Jobs are in the United Kingdom?

Data Idols are partnering with a leading UK retailer embarking on a significant AI transformation. They are looking for a Staff Platform Engineer - AI to design and build the secure, scalable platform capabilities that will underpin enterprise AI adoption across the organisation.

This role sits at the heart of a major technology transformation, offering the opportunity to build the cloud-native platforms, shared services and engineering foundations that will power the next generation of AI products and intelligent applications.

As a Staff Platform Engineer, you'll combine deep technical expertise with platform leadership, designing and delivering reusable cloud-native capabilities that enable AI at enterprise scale. You'll take ownership of complex technical challenges, building secure, high-performance platform services, APIs and integrations that accelerate the development of modern AI applications.

Working closely with Architecture, Product and Engineering teams, you'll define engineering standards, influence platform strategy and ensure AI workloads are scalable, resilient and production-ready. This is a highly hands-on role where you'll help shape the core platform that enables engineering teams to deliver AI solutions faster, more securely and more consistently.

• Strong experience designing and building cloud-native platforms on Azure
• Commercial experience with Databricks, Azure AI services, APIs and integration technologies
• Expertise developing scalable platform architecture and reusable engineering capabilities
• Experience supporting modern AI workloads, including LLMs, RAG and AI-powered applications
• A passion for technical leadership, engineering excellence and building platforms that enable teams to deliver at scale

If you're looking for a role where you can shape the future of enterprise AI by building the platforms that power next-generation intelligent applications, please submit your CV for initial screening and further details.

Entity:

Job Family Group:

Job Description:

bp is an equal opportunity employer. We believe that diversity and inclusion drive innovation and are crucial to our success. We welcome applications from all qualified individuals regardless of race, colour, religion, gender, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected characteristic.
 

We are committed to making reasonable adjustments for candidates with disabilities or long-term conditions. If you require any adjustments during the recruitment process, please let us know.
 

We are seeking an exceptional Staff Machine Learning Engineer to serve as a technical leader and architect of machine learning systems across the organisation.
 

This is the highest individual contributor tier within the field — a role for engineers and scientists who not only build world-class ML systems but define how they are built. You will shape architectural direction, establish engineering and scientific standards, and drive the delivery of complex, high-impact ML products that span the journey from research and experimentation through to solutions.
 

A core differentiator of this role is deep applied machine learning science: the ability to develop, validate, and deploy novel ML algorithms and scientific models as reliable, maintainable products — bridging the gap between innovative research and enterprise-scale deployment. You will influence multiple teams, mentor senior engineers, and drive step-change impact across business-critical, scientific, and R&D domains.
 

• Provide technical leadership in the design and architecture of large-scale, production-grade ML systems and platforms across the organisation.
• Own end-to-end delivery of complex ML solutions — from scientific problem framing and algorithm design through to deployment, operationalisation, and product delivery.
• Apply advanced machine learning science to develop novel algorithms and models, ensuring they are rigorously validated and deployed as scalable, reliable, production-grade products.
• Bridge the gap between scientific research and enterprise deployment — taking ML innovations from experimentation through to productised, maintainable solutions that deliver measurable value.
• Drive engineering excellence across ML systems, including CI/CD, testing, observability, reliability, and MLOps guidelines.
• Define technical standards, patterns, and protocols for ML engineering and applied ML science across teams.
• Lead complex, multi-team technical initiatives and influence organisational direction through technical authority.
• Evaluate and integrate emerging approaches — including generative AI, Agentic AI, advanced optimisation, and scientific computing — into scalable solutions.
• Supply to and shape internal ML platforms, reusable frameworks, and shared scientific computing capabilities.
• Mentor senior engineers and data scientists, raising the technical bar across the subject area.
• Partner with business and scientific customers to shape ML strategy and identify high-value opportunities.
• Present technical strategies, architectural decisions, and outcomes to senior leadership.
   

Essential

• MSc, PhD degree or equivalent experience in a quantitative field (e.g. Computer Science, Mathematics, Physics, Engineering, or related subject area).
• Hands-on experience designing, prototyping, productionizing, and scaling complex ML systems in production environments.
• Deep and demonstrable expertise in machine learning algorithms, statistical modelling, optimisation techniques, and scientific computing — with a consistent record of applying these to deliver production-grade products.
• Strong software engineering and system design expertise, including distributed systems, scalable architectures, and API design.
• Advanced programming experience in languages such as Python, Go, Java, or C++.
• Advanced SQL knowledge.
• Strong experience with MLOps, production ML systems, model lifecycle management, and monitoring.
• Experience working with large-scale data systems and distributed computing frameworks (e.g. Spark, Hadoop).
• Knowledge of experimental design, scientific methodology, and analysis.
• Strong partner management and confirmed ability to influence large organisations without direct authority.
• Demonstrated ability to lead through technical excellence and deliver high-impact, organisation-wide outcomes.
• Continuous learning and improvement approach.
   

• Deep experience in applied machine learning science — including developing novel algorithms and translating scientific research into deployable, production-grade ML products.
• Experience applying AI/ML to scientific, engineering, or R&D workflows — encompassing experimentation, simulation, optimisation, physics-informed modelling, and autonomous scientific workflows.
• Strong experience with generative AI (LLMs, RAG, multimodal systems) and their deployment in production.
• Experience designing or deploying Agentic AI systems — including autonomous agents, tool use, multi-agent orchestration, reasoning workflows, and agent-driven scientific discovery.
• Consistent record of innovation through publications in peer-reviewed venues, invention disclosures (IDFs), patents, or open-source contributions in machine learning or AI.
• Experience building ML platforms, reusable scientific computing frameworks, or internal tooling that accelerates delivery across teams.
• Familiarity with model interpretability, uncertainty quantification, and advanced experimental frameworks.
• No prior experience in the energy industry required.
   

(Complete by TA / HR with local benefits and compensation details)

• Competitive compensation and benefits package.
• Opportunity to lead and shape the future of ML and AI at one of the world's largest energy companies.
• A culture that values scientific difficulty, engineering excellence, and continuous learning.
• Hybrid working arrangements and a commitment to work-life balance.
• Career development pathways in a world-class technology organisation.
   

Please note that roles based out of SJS or Sunbury will move to Timber Square, Southwark, from Q4 2027
 

Travel Requirement

Relocation Assistance:

Remote Type:

Skills:

Legal Disclaimer:

We are an equal opportunity employer. We do not discriminate on the basis of protected characteristics like race, religion, color, sex, national origin, sexual orientation, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp’s recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please  contact us .

If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.

Entity:

Job Family Group:

Job Description:

bp is an equal opportunity employer. We believe that diversity and inclusion drive innovation and are essential to our success. We welcome applications from all qualified individuals regardless of race, colour, religion, gender, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected characteristic.
 

We are committed to making reasonable adjustments for candidates with disabilities or long-term conditions. If you require any adjustments during the recruitment process, please let us know.
 

We are looking for a Senior Machine Learning Engineer who combines deep machine learning expertise with strong software engineering subject area to design, build, and deploy production-grade ML and AI systems.
 

This role goes beyond traditional ML engineering. You will apply machine learning science as a core field — developing novel algorithms and models that are not only experimentally validated but architected and deployed as scalable, reliable products. Whether it's advancing NLP, optimisation, simulation, or generative AI, you will deliver solutions that transition seamlessly from research to production and create measurable value.
 

You will work as part of a cross-disciplinary team alongside data scientists, software engineers, data engineers, and domain authorities — translating complex scientific and business problems into deployable ML products.
 

• Design, build, and maintain scalable, production-grade machine learning systems and pipelines using modern engineering practices (CI/CD, testing, monitoring, observability).
• Apply machine learning science to develop novel algorithms and models that are deployed as reliable, scalable products — not limited to experimentation but extending through to production delivery and operational use.
• Build impactful ML products demonstrating statistical modelling, deep learning, and AI techniques across operational, scientific, and R&D domains.
• Translate complex scientific and business problems into well-scoped ML solutions, delivering actionable insights and deployable capabilities.
• Architect and optimise ML systems for performance, scalability, and reliability in production environments.
• Collaborate closely with data scientists, data engineers, software engineers, and domain authorities as part of cross-disciplinary teams.
• Adhere to and advocate for engineering and data science guidelines (technical design, design reviews, unit testing, monitoring & alerting, code reviews, documentation).
• Present technical results, trade-offs, and product outcomes to peers and senior partners.
• Actively supply to improving developer velocity, engineering standards, and shared tooling.
• Mentor junior team members and chip in to the technical growth of the wider team.
   

Essential

• MSc, PhD degree or equivalent experience in a quantitative field (e.g. Computer Science, Mathematics, Physics, Engineering, or related discipline).
• Hands-on experience designing, prototyping, productionizing, maintaining, and scaling ML/data science products in complex environments.
• Strong and demonstrable expertise in machine learning algorithms, statistical modelling, and optimisation techniques — with a track record of applying these to build production-grade solutions.
• Applied knowledge of data science and ML tools across all stages of the data and model lifecycle.
• Thorough understanding of the mathematical foundations of statistics, machine learning, and scientific computing.
• Strong programming experience in one or more object-oriented languages (e.g. Python, Go, Java, C++).
• Advanced SQL knowledge.
• Experience with modern ML engineering practices including MLOps, model lifecycle management, CI/CD, and monitoring.
• Knowledge of experimental design, analysis, and scientific methodology.
• Customer-centric and pragmatic mentality with a focus on value delivery and swift execution, while maintaining rigour and attention to detail.
• Strong partner management and ability to influence across teams and organisations.
• Continuous learning and improvement mentality.
   

• Experience with big data technologies (e.g. Hadoop, Hive, Spark).
• Experience with generative AI, LLMs, or retrieval-augmented generation (RAG).
• Exposure to Agentic AI concepts, including autonomous agents, tool use, and orchestration frameworks.
• Experience applying machine learning and AI to scientific or R&D workflows — with emphasis on building deployable ML products from scientific research (e.g. simulation, optimisation, physics-informed models).
• Familiarity with model interpretability, uncertainty quantification, and advanced experimental methodologies.
• Consistent track record of publications, invention disclosures (IDFs), or patents in machine learning or AI.
• No prior experience in the energy industry required.
   

(Complete by TA / HR with local benefits and compensation details)

• Competitive compensation and benefits package.
• Opportunity to work on innovative ML and AI problems at global scale.
• A culture that values scientific rigour, engineering excellence, and continuous learning.
• Hybrid working arrangements and a commitment to work-life balance.
• Career development pathways in a world-class technology organisation.
   

Please note that roles based out of SJS or Sunbury will move to Timber Square, Southwark, from Q4 2027
 

Travel Requirement

Relocation Assistance:

Remote Type:

Skills:

Legal Disclaimer:

We are an equal opportunity employer. We do not discriminate on the basis of protected characteristics like race, religion, color, sex, national origin, sexual orientation, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp’s recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please  contact us .

If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.

Senior Machine Learning Operations (MLOPS) Engineer

Contract Type: Permanent

Location: Alderley Park (Wilmslow)

Working Style: Hybrid - 50% from home / 50% office based

We have an exciting opportunity for a Senior Machine Learning Operations Engineer to join Royal London’s Group Data and AI Office. In this role, you’ll provide senior technical leadership for the workflows, tooling and engineering practices that take machine learning safely and reliably from experimentation into production.

Working closely with data scientists, data engineers and platform teams, you’ll define and evolve standards for CI/CD, experiment tracking, model lineage and controlled promotion across environments. Using Databricks, MLflow and Azure ML, you’ll help create scalable, well-governed pipelines that are reproducible, traceable and auditable.

You’ll also embed model risk management into delivery, supporting repeatable builds, clear lineage, transparent decision points and audit trails that strengthen governance and reduce operational risk.

As a senior practitioner, you’ll champion engineering excellence, reusable patterns and production-ready ways of working. You’ll mentor colleagues, support communities of practice and influence platform and architecture decisions so ML products deliver sustainable business value at scale.

• Design and evolve scalable, production-grade ML workflows on Databricks.
• Lead effective use of MLflow for experiment tracking, model versioning, lineage and lifecycle management.
• Build reusable CI/CD patterns for model training, validation, promotion and inference.
• Champion strong engineering practices, including modular Python, testing, reproducibility and configuration management.
• Work with data scientists and platform teams to productionise models safely and efficiently.
• Mentor colleagues and support high standards across the team.

• Strong experience with Azure, including Azure ML, Data Factory and Azure DevOps.
• Hands‑on experience with Databricks, MLflow and production‑grade ML workflows.
• Experience designing CI/CD pipelines using Azure DevOps, GitHub Actions or similar tools.
• Advanced Python skills, with knowledge of SQL, Spark and testing approaches for ML.
• Understanding of data engineering concepts such as ETL/ELT, feature stores and lineage tracking.
• Awareness of security, governance, Responsible AI and relevant AI regulation.

If you feel you’d be a great fit for Royal London but don’t meet every requirement, we’d still love to hear from you!

We’re the UK’s largest mutual life, pensions and investment company, offering protection, long‑term savings and asset management products and services.

Our People Promise is to make Royal London inclusive, responsible, enjoyable and fulfilling, underpinned by our Spirit of Royal London values: Empowered, Trustworthy, Collaborate and Achieve.

We offer great benefits, including 28 days’ annual leave plus bank holidays, up to 14% employer pension matching and private medical insurance.

We’re an inclusive employer and welcome applications from people of all backgrounds. We value the different perspectives, experiences and skills our colleagues bring.

Role

Senior Staff Machine Learning Engineer to own pricing ML within Rosso. This is a hands‑on senior IC role with real technical authority – you set the strategy, define the mathematical approach, build the models, and ship them. You work closely with MLOps and software engineers, but you don’t wait on them. The hard part of this job is the formulation, not the infrastructure.

• Own the technical direction for pricing ML. Define what to build and how. Set the roadmap for the pricing engine as a core piece of tem’s IP – and be accountable for its performance.

• Formulate and solve the pricing problem properly. The mathematical foundation doesn’t fully exist yet. Your first job is to define it: a dynamic, real‑time system that simultaneously optimises for signing probability, portfolio balance, and margin. Choose the right approach – stochastic programming, reinforcement learning, classical ML, or a hybrid – based on the problem, not familiarity.

• Build and ship models end‑to‑end. Own the modelling and data layer. Write production‑grade Python. Architect models with deployment in mind and carry them through to production – you can execute without being blocked by engineering dependencies.

• Solve imbalance problems. Develop probabilistic models to optimise risk management and short‑term balancing decisions in a highly dynamic environment.

• Be the voice of pricing ML across the business. Commercial, product, and engineering teams depend on this engine. They need to understand what it’s doing and why. You make that happen – clearly, without losing precision.

• Deep experience building ML systems for pricing, revenue optimisation, or real‑time decision‑making – at companies where pricing is the product, not a supporting function. Track record of models that reached production and moved commercial metrics.

• Strong foundation in stochastic optimisation and probabilistic modelling. The judgement to formulate ambiguous business problems mathematically before reaching for a tool.

• First‑principles reasoning across methods. You choose between stochastic programming, reinforcement learning, classical ML, or a simple heuristic based on what the problem demands.

• The engineering depth to match your modelling. Production‑grade Python, high bar for code quality, and the ability to carry models from formulation to deployment without being blocked.

• Senior technical leadership. A track record of setting direction for a significant technical area, influencing cross‑functional teams, and translating complex model behaviour into clear terms for commercial, product, and engineering stakeholders – so decisions are understood and acted on.

• Experience with real‑time pricing at scale – ride‑hailing, food delivery, logistics, or similar environments where latency and portfolio effects matter.

• Familiarity with energy markets, power trading, or portfolio risk management.

• PhD or equivalent research depth in a quantitative discipline – statistics, applied mathematics, operations research, or similar.

• Ability to reason about trade‑offs between optimisation solvers (Gurobi etc.) and gradient‑based methods (PyTorch etc.), and the judgement to know when to reach for each.

• Experience with causal inference or reinforcement learning in applied commercial settings.

We welcome applications from people of all backgrounds, experiences, and identities, including those that are traditionally underrepresented in the tech and energy sectors. If you’re excited about this role but not sure you meet every requirement, we’d still love to hear from you. Your unique perspective could be exactly what we’re looking for.

Established in 1997 as the first manufacturer of sushi for the UK supermarket industry, Taiko has evolved into the most innovative manufacturer of Sushi, Food To Go, Prepared Meals and Snacking products in the UK, supplying Waitrose, Tesco and Sainsbury’s to name a few. Over the past 25 years Taiko has launched more first to market Sushi and Food to Go products than any other sushi manufacturer in the UK.

We’re looking for a Sushi-focused Development Chef with a passion for flavour, innovation, and customer-led development.

This role is all about pushing boundaries—developing standout Sushi products with exciting flavour profiles, blending authenticity with modern, trend‑led influences. You’ll work cross‑functionally with NPD, Commercial, Marketing, and Operations teams to bring new ideas to life at scale.

Working pattern: Monday to Friday – giving you consistency while still working in a fast‑paced, creative environment.

• Experienced Sushi Chef (essential) with strong technical expertise
• Deep understanding of flavour balance, seasoning, and Sushi composition
• Passionate about innovation and pushing flavour boundaries
• Confident presenting to customers and bringing ideas to life
• Commercially aware with the ability to scale concepts into production
• Hands‑on, organised, and thrives in a creative, fast‑paced environment

• Create innovative Sushi concepts with a strong focus on flavour development and differentiation
• Translate customer briefs into unique, trend‑led Sushi products
• Experiment with fusion flavours, global influences, and new ingredient pairings
• Deliver impactful customer presentations, telling the story behind your flavour concepts
• Develop recipes that balance flavour, cost, and scalability
• Prepare samples for tastings, food shows, and key customer meetings
• Conduct flavour benchmarking and competitor analysis
• Support factory scale‑up, maintaining flavour integrity in production
• Continuously refine and elevate existing Sushi ranges

• Opportunity to grow your career alongside with us with available apprentice program
• Brilliant support services designed to enhance your physical, mental and financial wellbeing.
• Annual discretionary bonus subject to business and overall performance
• Discretionary Life Assurance
• Discretionary Income Protection
• Private Medical Cash Plan
• Bespoke reward platform including access to retail, cinema & gym discounts.
• 50% off your food every time you dine with us for you and 3 friends.
• Contribute towards our award‑winning sustainability initiatives that delivers progress against 9 UN sustainability goals. We’re committed to responsibly sourcing and all our seafood, therefore we only use source sustainable fish. All our packaging is recyclable and 80% of our packaging is already made from recycled plastic.
• Annual Awards ceremony celebrating our success and offering winning Managers free trips to Japan.

Come roll with us and be part of something big. Celebrate global success across:

• Over 1500 retail kiosks globally (YO!, Panku, Mai Taiko Snowfox & Bento)
• Our Taiko manufacturing and distribution centre
• 63 YO! restaurants
• 3700 locations globally From Hawaii to Aberdeen

• Think like an owner. Be passionate. Speak openly. Move fast, together.

Come roll with us and play a key role by bringing people together to celebrate better food for everyone the Japanese way.

About the Role

Data scientists on FTI's AI Build Team should have a pragmatic approach to problem‑solving and be capable of developing end‑to‑end solutions that clients can rely on in production. They should be capable of challenging their own work and finding a balance between perfection and practicality. FTI's AI build team is technology‑agnostic with software engineering expertise to deploy advanced ML/AI methodologies at scale. Our engagements include using NLP for automated document classification, geospatial modeling of electric vehicle demand, demand forecasting, predictive maintenance, price optimization, and developing and maintaining production‑grade agentic RAG systems that serve the entire firm.

• Data Management
  • Perform data availability/quality assessments
  • Develop comprehensive ETL processes
• Data Analysis
  • Perform exploratory data analysis and render key insights through evidenced results
  • Execute data quality assessments
  • Illustrate material understandings through coherent data visualizations
  • Execute and tune statistical analyses
• Modeling
  • Conduct necessary research for proof‑of‑concept model selection
  • Identify viable model features and apply appropriate normalizations
  • Appropriately log model parameters and metrics for comparison
  • Diligently optimize current processes and pipelines
  • Perform quality control
  • Actively work on ModelOps design and implementation
• Engineering
  • Develop data pipelines and models that are well designed and auditable
  • Develop production‑ready code that is scalable, maintainable, and adheres to best design principles
  • Develop scalable Gen AI solutions
• Communication
  • Frequently partner with internal and external stakeholders both technical and non‑technical
  • Provide guidance to junior data scientists

We are committed to investing and supporting you in your professional development. We have developed a range of programs focused on fostering leadership, growth and development opportunities. Our programs promote continuous learning and individual skills development through on‑the‑job learning, self‑guided professional development courses and certifications. You’ll be assigned a dedicated coach to mentor, guide and support you through regular coaching sessions and serve as an advocate for your professional growth. As you progress through your career at FTI Consulting, we offer tailored programs for critical professional milestones to ensure you are prepared and empowered to take on your next role.

Experience in ideating a proof‑of‑concept and independently managing workstreams in larger projects.

Experience in mentoring junior resources.

• Bachelor's degree in Math, Physics, Computer Science, Statistics, or equivalent qualifications
• A couple of years of data science experience
• Ability to travel to clients and FTI office(s)

• Proficiency in Python including in depth knowledge of object‑oriented programming and design principles
• Proficiency in SQL including strong knowledge of database structure and efficiency
• Proficiency in Git
• Proficiency in AI/ML frameworks: Huggingface, Torch, TensorFlow, Scikit‑Learn, and Spacy
• Experience in MLOps platforms: MLFlow, dbt, Docker, Kubernetes
• Experience with cloud environments such as AWS

• Experience in NLP, Forecasting, Clustering, Recommendation Engines, Network Analysis (Graph Theory), and Regressions
• Experience in AI/ML concepts: Cross Validation, Ensemble Methods, Over/Under Fitting, Accuracy/Precision/Recall, RAG, Agents
• Understanding of AI/ML performance measurement best practices including QA/QC framework, drift, bias, and fairness
• Experience in computer science concepts: Hashing, Space Complexity, and Parallel Processing (Multiprocessing)
• Ability to work with Linux/*nix systems, bash scripting, SSH (with some instruction)
• Experience in a Solution Architect role, with a demonstrated ability to design technical solutions including Database Design, ModelOps, and Orchestration

FTI Consulting is an equal opportunity employer and does not discriminate on the basis of race, color, national origin, ancestry, citizenship status, protected veteran status, religion, physical or mental disability, marital status, sex, sexual orientation, gender identity or expression, age, or any other basis protected by law, ordinance, or regulation.

At Graphcore, we’re building the future of AI compute.

We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.

As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems.

The Software Infrastructure team provides critical platforms and services for software development teams across the business. Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems. We operate in squads, fostering a culture of service ownership and empowerment for our engineers. We focus on long-term engineering solutions and strive to eliminate toil wherever possible.

• Develop, own, and maintain tools and services to support AI research and engineering teams.
• Deploy and maintain services with Kubernetes and Docker.
• Manage our Cloud Infrastructure using tools such as Terraform.

• Knowledge of Python.
• Familiarity with cloud services (e.g. AWS).
• Experience managing or developing in Linux environments.
• Understanding of CI/CD principles.
• Experience maintaining machine learning applications.
• Experience deploying ML orchestration tools (e.g. NV Ray, KFP, SkyPilot).
• Experience managing ML accelerator hardware (e.g. DCGM).
• Experience with Infrastructure as Code (IaC) tools (e.g. Terraform/OpenTofu).
• Experience with GitHub Actions.
• Experience with modern observability tooling (e.g. Prometheus).
• Experience with Grafana.
• Knowledge of Go/Java/C++ (or similar language).

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.