At a Glance
- Tasks: Transform AI/ML prototypes into reliable, scalable production systems that impact real-world applications.
- Company: Join an award-winning tech company focused on innovation and professional growth.
- Benefits: Enjoy competitive salary, hybrid work, healthcare, and extensive training opportunities.
- Other info: Dynamic environment with excellent career growth and mentorship opportunities.
- Why this job: Be at the forefront of AI/ML engineering and make a tangible difference in technology.
- Qualifications: Strong Python skills and experience in backend/API engineering are essential.
The predicted salary is between 80000 - 100000 £ per year.
Great AI and machine learning capability only creates value once it runs reliably in the real world.
This role exists to bridge that final, critical gap—taking the AI/ML solutions developed within our Data Science team from promising prototypes to robust, scalable production systems that our teams and customers depend on every day.
Sitting within Data Science, this is at heart a hands‑on AI/ML engineering role. Your primary focus will be productionising Generative AI and agentic systems —building the APIs, tools, integrations and workflows that let LLMs, and agents operate reliably at scale.
You will also support the broader range of machine learning models and pipelines across the business.
You will be the key partner working hand in hand with Engineering, Dev Ops and Infrastructure teams to bring our models and systems into production—owning the technical journey of making AI/ML systems live, stable, secure and performant.
As a senior member of the Data Science team, you will set the standard for production readiness, act as the bridge between data science and the wider engineering organisation, drive delivery across teams, and mentor colleagues.
Your work will directly determine how quickly and confidently Argus can bring new AI/ML capabilities to life.
- What Will You Be Doing
- Delivery & Engineering
- Design and build robust, secure APIs and backend components that power AI/ML, Gen AI and agentic applications.
- Engineer agentic systems—integrating LLMs with tools, data sources, and business workflows into reliable, production‑grade pipelines.
- Drive systems from prototype to production, owning reliability, scalability, and operational readiness.
- Raise code quality, structure, and production readiness across the AI/ML stack.
- Debug and resolve issues across APIs, environments, and integrations, ensuring rapid response times and minimal disruption.
- Act as the primary technical partner between Data Science and the Engineering, Dev Ops and Infrastructure teams, taking solutions from development through to live deployment.
- Advise and support colleagues across the business whose systems integrate with AI/ML and agentic components.
- Proactively resolve technical ambiguity to reduce delivery friction and rework, ensuring a smooth handover from prototype to production.
- Technical Leadership & Enablement
- Establish and evolve engineering standards for productionising AI/ML, including testing, observability, versioning, and release management.
- Mentor and guide data scientists and engineers, providing code reviews and hands‑on technical support.
- Champion a culture of disciplined engineering, continuous improvement, and operational excellence within Data Science.
Skills And Experience
Education
A degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Science, or a related technical discipline—or equivalent hands‑on experience.
An MSc or Ph D is welcome but not essential.
Essential Experience & Skills
- Exceptionally strong Python programming skills, with a deep grasp of object‑oriented design, clean code, and core software engineering principles (e. g.
SOLID, design patterns, modularity, testability).
- Strong backend / API engineering experience, ideally in Python (e. g. Fast API, or similar).
- Hands‑on experience building and operating solutions in AWS environments.
- Proficiency with Docker, Git Hub, and CI/CD pipelines.
- Proven ability to partner with and work across teams to drive delivery into production.
- Strong problem‑solving, debugging, and performance optimisation skills.
- Solid software engineering foundations, including version control, automated testing, and monitoring.
- Experience building or productionising agentic AI systems—tool use, orchestration, multi‑step reasoning, or agent frameworks (e. g.
Lang Graph, Lang Chain, Crew AI, Auto Gen, or similar).
- Experience with Gen AI / LLM systems in a production context (RAG, prompt orchestration, evaluation, guardrails, cost/latency optimisation).
- Exposure to MCP (Model Context Protocol) and tool‑based / function‑calling architectures.
- Experience deploying and operating machine learning models / MLOps pipelines (e. g. model serving, monitoring, retraining workflows).
- Experience with real‑time / streaming systems.
- What’s In It For You
Our rapidly growing, award‑winning business offers a dynamic environment for talented, entrepreneurial professionals to achieve results and grow their careers.
Argus recognizes and rewards successful performance and as an Investor in People, we promote professional development and retain a high‑performing team committed to building our success.
- Competitive salary and company bonus scheme
- Group healthcare and life assurance scheme
- Hybrid working environment (currently three days in office)
- 25 days annual holiday with incremental increase up to 30 days
- Subsidised gym membership
- Season ticket travel loan
- Cycle to work scheme
- Flexible benefits platform (ability to buy additional medical cover, life assurance, dental cover, holiday, critical illness, travel insurance & health screening)
- Extensive internal and external training
- #J-18808-Ljbffr
Senior AI/ML Engineer in London employer: Argus Media
Argus is an excellent employer for an AI Automation Engineer, offering a dynamic work environment in London where innovation meets collaboration. With a strong focus on employee growth, Argus provides extensive training opportunities and a hybrid working model that promotes work-life balance. The competitive salary, comprehensive benefits package, and supportive culture make it an ideal place for professionals looking to make a meaningful impact in the energy and commodity markets.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI/ML Engineer in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Argus Media!
✨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 Senior AI/ML Engineer at Argus Media.
✨Leverage Professional Networks
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 Argus Media.
✨Apply Directly through Our Website
When you find a suitable opening like Senior AI/ML Engineer at Argus Media, 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 Senior AI/ML Engineer in London
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 Argus Media, 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 Argus Media. 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 Argus Media
✨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 Argus Media!
✨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.
