AI/ML Engineer in London

AI/ML Engineer in London

London Full-Time 70000 - 90000 £ / year (est.) Home office (partial)
Shell

At a Glance

  • Tasks: Design and build AI solutions that drive real business value.
  • Company: Join Shell, a global leader in energy and technology.
  • Benefits: Enjoy flexible hours, competitive salary, and remote work options.
  • Other info: Grow your career with diverse opportunities and a focus on inclusion.
  • Why this job: Make an impact with cutting-edge AI technologies in a collaborative environment.
  • Qualifications: Degree in Data Science or related field; experience in machine learning required.

The predicted salary is between 70000 - 90000 £ per year.

AI/ML Engineer role is focused on delivering production-scale AI and data solutions that drive business value across Shell’s end-to-end value chain. This role designs, builds, and operates full-stack data science, machine learning, and Generative AI applications on cloud-based digital platforms (Azure/AWS), working within agile product teams. The position requires strong ownership across the full product lifecycle, from model development to deployment, monitoring, and continuous improvement.

What you’ll be doing:

  • Data and Software Engineering in Data Science and Machine Learning (ML) drives business value through providing quality technical, functional and consulting expertise to deliver the right skills, at the right time, in the right place.
  • Create full-stack data science application and tools on a digital platform.
  • Responsible for delivery of data science tasks for a product in a production scale environment through Agile.
  • Understand the product lifecycle especially relating to data science, development to support.
  • Deepen knowledge of current and emerging AI Engineering practices and technologies and gain applicable certifications.

What you bring:

  • Bachelor or Master’s degree in quantitative subjects like Data Science, Computer Science, Applied Mathematics, Statistics, Physics, bringing significant years of experience in the industry.
  • Practical experience in developing end-to-end models using machine learning for predictive modelling in a business/industry environment, i.e., feature engineering, model creation, evaluation and postproduction support mechanisms.
  • Hands-on experience in building large scale distributed Machine Learning Applications using microservices and event driven systems-based practices.
  • Extensive experience in designing applications with Azure Machine Learning Services.
  • Technical Knowledge of MLOps principles and standards to build ML pipelines for automated model deployment, model performance monitoring, data drift detection in market standard platforms like Azure Machine Learning, AWS Sagemaker C3 or Databricks.
  • Strong interest and curiosity in exploring a wide range of languages, frameworks, and tools, including Python, PySpark, .NET/C#, Java, JavaScript, Kubernetes, and Kafka.
  • Experience in extracting, cleansing, and manipulating large, diverse structured and unstructured data sets and designing workflow or Orchestration systems such as ADF, Airflow, C3.ai, Databricks, Dagster, Datalake etc.
  • Must have a proven track record of architecting and launching a large-scale Generative AI platform from the ground up, with demonstrated reach of at least 20,000 customers and deep expertise in LangChain, LangGraph, and Microsoft Agent Framework.
  • Must have led end-to-end development and CI/CD deployment of production-grade, multi-agent autonomous systems leveraging A2A protocols and MCP servers, ideally on Microsoft AI Foundry and Microsoft Agent Service, including the establishment of both offline and online evaluation frameworks.
  • Must have designed and delivered enterprise-scale Text-to-SQL solutions with a strong command of natural language interfaces for structured databases, leveraging Mosaic and Genie.
  • Must have built and shipped enterprise-grade RAG solutions with advanced context engineering, incorporating Agent Skills, sophisticated chunking strategies, and document intelligence pipelines for multimodal RAG — including data extraction using Mistral Doc AI.
  • Must have designed and implemented a robust test harness for LLM model benchmarking and comparison.
  • Skilled in at least one of the following: GenAI, LLM models, ML algorithms, Machine Vision, NLPC3, including JavaScript, data ingestion, integration, model management and monitoring, API framework, prebuilt libraries Cloud Application development, deployment, and monitoring on platforms like Azure, AWS.
  • Deep knowledge of the technology landscape and context in one or more Shell core business areas, e.g. SSW, IGUPT, RES, etc.
  • Passionate and experienced in working with small, empowered, cross-functional teams focused on delivery.
  • Possesses strong interpersonal skills for both teamwork and independent work, and is adept at collaborating with virtual teams and stakeholders in agile environments.

What we offer:

  • You bring your skills and experience to Shell and in return you work with talented, committed people on one of the most important challenges facing our planet.
  • You’ll have the opportunity to develop the skills you need to grow in an environment where we value honesty, integrity, and respect for one another.
  • You’ll be able to balance your priorities as you become the best version of yourself.
  • Continuously grow the transferable skills you need to get ahead.
  • Work at the forefront of technology, trends, and practices.
  • Collaborate with experienced colleagues with unique expertise.
  • Achieve your balance in a values-led culture that encourages you to be the best version of yourself.
  • Make an impact in one of the world’s leading technology-driven businesses.
  • Benefit from flexible working hours, and the possibility of remote/mobile working.
  • Perform at your best with a competitive starting salary and annual performance related salary increase – our pay and benefits packages are considered to be among the best in the world.
  • Take advantage of paid parental leave, including for non-birthing parents.
  • Join an organisation working to become one of the most diverse and inclusive in the world.
  • Grow as you progress through diverse career opportunities in national and international teams.
  • Gain access to a wide range of training and development programmes.

Shell is working to advance an inclusive, psychologically safe and accessible environment where people with disabilities can excel. If you require any accommodations or accessibility adjustments (e.g. assistive technology, communication support, any other) during the application or interview process, please let us know directly via careers@shell.com. We strive to ensure that our process and workplace is accessible to everyone and are dedicated to making reasonable adjustments to support your needs.

Shell in The United Kingdom is a vital contributor to the UK, supporting energy security, jobs and economic value. We provide energy to fuel homes, hospitals, schools, vehicles, machinery and factories. Our history here dates back over 125 years. A UK-headquartered global energy leader, and leading FTSE multinational, we are active across the country’s energy system.

In the years ahead, as the UK looks to strengthen energy security and deliver its 2050 net-zero goal, Shell UK aims to play a crucial role. We aim to be a major investor in the UK energy system by helping our customers decarbonise with a focus on transport and industry.

AI/ML Engineer in London employer: Shell

At Shell, we pride ourselves on being an exceptional employer, offering AI/ML Engineers the chance to work at the forefront of technology in a collaborative and inclusive environment. Our commitment to employee growth is evident through diverse career opportunities, extensive training programmes, and a culture that values honesty, integrity, and respect. With flexible working arrangements and competitive benefits, including paid parental leave and a focus on work-life balance, Shell is dedicated to helping you become the best version of yourself while making a meaningful impact in the energy sector.

Shell

Contact Details:

Shell Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI/ML Engineer in London

Get Involved in Data Science Meetups

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Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI/ML Engineer at Shell.

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Shell.

Apply Directly through Our Website

When you find a suitable opening like AI/ML Engineer at Shell, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace AI/ML Engineer in London

Python
SQL
Data Engineering
Problem-Solving Skills
Communication Skills
Data Pipeline Development
API Integration

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Shell, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Shell. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Shell

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Shell!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.