Senior AI/ML Engineer

Argus Media; Greater London; Hybrid; GBP 110,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

Group pension scheme

Group healthcare and life assurance

Hybrid working environment

25 days annual holiday

Subsidised gym membership

Season ticket travel loan

Cycle to work scheme

Flexible benefits platform

Internal and external training

Job summary

Argus Media is hiring a senior AI/ML engineer in London to bridge prototypes and production. You will productionise Generative AI, build APIs, tools and workflows enabling LLMs and agents to run reliably at scale, and partner with Engineering, DevOps and Infrastructure.

You will mentor colleagues, set standards for production readiness, and shape how quickly Argus can bring new AI capabilities to life. This hands-on role requires strong Python, API, AWS, Docker and CI/CD skills, plus

Qualifications

• Exceptionally strong Python programming skills with solid OOP and SOLID
• Backend/API engineering experience in Python (FastAPI or similar)
• Hands-on AWS experience
• Proficiency with Docker, GitHub, and CI/CD pipelines
• Proven ability to partner with cross‑team to drive production delivery
• Strong debugging and performance optimization skills
• Solid software foundations including version control, automated testing and monitoring

Responsibilities

• Design and build robust, secure APIs and backend components powering AI/ML, GenAI and agentic apps
• Engineer agentic systems—integrating LLMs with tools and data into reliable pipelines
• Drive systems from prototype to production, focusing on reliability and scalability
• Raise code quality and production readiness across the AI/ML stack
• Debug and resolve issues across APIs, environments, and integrations for rapid response

Skills

Python

Backend API

AWS

Docker

GitHub

CI/CD

Collaboration

Debugging

Performance tuning

Education

Degree in CS/AI/ML

Tools

FastAPI

Job description

What We’re Looking For

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, DevOps 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, GenAI 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.

Collaboration & Partnership

• Act as the primary technical partner between Data Science and the Engineering, DevOps 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 PhD 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. FastAPI, or similar).
• Hands‑on experience building and operating solutions in AWS environments.
• Proficiency with Docker, GitHub, 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.

Desirable

• Experience building or productionising agentic AI systems—tool use, orchestration, multi‑step reasoning, or agent frameworks (e.g. LangGraph, LangChain, CrewAI, AutoGen, or similar).
• Experience with GenAI / 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

• Competitive salary and company bonus scheme
• Group pension 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

Argus is the leading independent provider of market intelligence to the global energy and commodity markets. We offer essential price assessments, news, analytics, consulting services, data science tools and industry conferences to illuminate complex and opaque commodity markets.

Headquartered in London with 1,500 staff, Argus is an independent media organisation with 32 offices in the world’s principal commodity trading hubs.

Companies, trading firms and governments in 160 countries around the world trust Argus data to make decisions, analyse situations, manage risk, facilitate trading and for long‑term planning. Argus prices are used as trusted benchmarks around the world for pricing transportation, commodities and energy.

Founded in 1970, Argus remains a privately held UK-registered company owned by employee shareholders and global growth equity firm General Atlantic.