AI/ML Engineer

Argus Media; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid working (1 day in office)

25 days annual holiday

Group healthcare & life assurance

Gym membership subsidy

Season ticket travel loan

Cycle to work scheme

Training & personal development

Job summary

Argus Media in London is seeking an hands-on AI/ML engineer to productionise Generative AI and agentic systems, building APIs, tools and workflows that let LLMs operate reliably at scale. You will partner with Engineering, DevOps and Infrastructure to bring models to production with reliability, security and performance.

In Data Science, you will set standards for production readiness, mentor colleagues, and drive delivery across teams, shaping how quickly Argus can deploy new AI capabilities to

Qualifications

• Degree in Computer Science, AI, ML, Software Engineering, Data Science or equivalent hands-on exp.
• MSc/PhD welcome but not essential.
• Strong Python and backend/API engineering experience.

Responsibilities

• Design and build robust APIs and backend components for AI/ML applications.
• Engineer agentic systems—integrating LLMs with tools, data sources, and workflows.
• Drive production readiness, reliability and observability across the stack.
• Mentor data scientists and engineers and advocate disciplined engineering.

Skills

Python programming

Backend API engineering

AWS experience

Docker

CI/CD pipelines

Cross-team collaboration

Debugging & performance

Software fundamentals

Agentic AI systems

GenAI/LLM production

MCP exposure

MLOps pipelines

Real-time/streaming

Education

Bachelors in CS/AI/DS/SE

MSc or PhD welcome

Tools

LangGraph

LangChain

CrewAI

AutoGen

Job description

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 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.
• Act as the 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.
• 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 healthcare and life assurance scheme
• Hybrid working environment (currently one day 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.