AI Engineer

Beamery; London; On-site; GBP 50,000 - 85,000; Full time

Job summary

Beamery is looking for a hands-on machine learning practitioner to join their team in London. The role involves building and deploying intelligent ML products centered on LLMs and agentic workflows, transforming complex talent data into actionable insights. We're seeking individuals with proven experience delivering ML projects, strong foundations in NLP, and familiarity with software engineering best practices. Join us to shape the future of workforce planning and talent intelligence.

Qualifications

• Proven experience with the full ML project lifecycle.
• Strong foundation in NLP, LLMs, and Transformers.
• Experience with search and recommendation systems.

Responsibilities

• Build and deploy ML systems for talent management.
• Transform customer data into actionable insights.
• Prototype models and assess feasibility for innovation.

Skills

Natural Language Processing

Machine Learning

Model Fine-tuning

Transformers

Recommendation Systems

Tools

Python

SQL

MongoDB

Docker

Google Cloud Platform

Kubernetes

Job description

ABOUT BEAMERY

Beamery's mission is to create equal access to work, skills, and careers. We are a leading transformational AI platform in the HR technology industry, enabling enterprise companies to create better and fairer talent decisions - by accelerating their recruiting processes, unlocking successful internal mobility opportunities, enabling smarter upskilling initiatives, and facilitating agile workforce planning. We are helping our clients hire and redeploy over a million people annually.

Our product is used by Fortune 2000 organizations globally and enables users across 100+ countries to make smarter talent decisions and close skills gaps. Read more about our work here.

What's ahead - and why it's an exciting time to join the team:

Deepening our native integrations with SAP, Workday, Microsoft, and LinkedIn to seamlessly embed our skills intelligence into the platforms where critical workforce decisions are made.

Embedding our agentic AI to help customers plan smarter for the future-powering workforce strategies, internal mobility, and skills forecasting.

Advancing our use of proprietary LLMs and knowledge graph technology to help organizations unlock broader talent pools, make fairer decisions, and expand access to opportunity at scale.

But it's not all about creating high-quality products, we also very much value the company culture we have worked hard to create; built on trust, empathy & honesty ensuring our workforce is able to bring their full selves to work.

ABOUT THE TEAM
Beamery Edge creates a data-and-computation environment for large-scale experimentation with unique data assets. We combine data, analytics, and science to build a multimodal knowledge base that draws on both structured and unstructured sources, enabling solutions such as information extraction, entity resolution, graph-based embeddings, and search. You will be part of a hands-on, globally distributed group tackling novel R & D problems that directly impact customers.

OUR TECHNOLOGY STACK: Python • Agentic tools (Autogen, Semantic Kernel, LangChain) • SQL • MongoDB • Third-party LLM APIs • LiteLLM • MLflow • Google Cloud Platform • Docker • PyTorch • Hugging Face Transformers • SPARQL • Kubernetes

WHAT YOU WILL BE DOING AT BEAMERY
Join us at the forefront of transforming how organisations manage talent and plan their workforce. We're building intelligent products powered by LLMs and agentic workflows that turn complex talent data into actionable insights and automation.

Build and deploy ML systems that process and reason over complex, semi-structured text to enhance the end-to-end talent management experience for customers.
Transform customer data into actionable insights through machine learning, surfacing patterns that unlock new product features and opportunities.
Continuously explore emerging research in LLMs, multi-agent workflows, retrieval-augmented generation (RAG), recommendation systems, and model evaluation, bringing fresh ideas into our product roadmap.
Prototype quickly and creatively: experiment with new models, techniques, and data signals to assess feasibility and accelerate innovation.
Work closely with software teams to integrate ML capabilities into production systems with reliability and scale.
Design robust evaluation pipelines and datasets to rigorously test model performance and track real-world impact over time.

WHO ARE WE LOOKING FOR?
You're a hands-on machine learning practitioner who thrives on building real-world solutions. You're excited by the opportunity to work on impactful GenAI products and ready to help shape what's next in workforce planning and talent intelligence.
We'd love to hear from you if you have:

Proven experience delivering ML projects across the full development lifecycle, from experimentation and evaluation to production deployment.
Comfort with ambiguity, and the ability to shape early-stage product ideas in fast-evolving domains.
Strong foundation in NLP and GenAI, including experience with Transformers, LLMs, RAG (retrieval augmented generation) pipelines, agents, and model fine-tuning.
Familiarity with search and recommendation systems, and how to build ML solutions that deliver relevance and value.
A solid grasp of software engineering best practices, including CI/CD workflows, testing, and scalable ETL pipelines.
The ability to collaborate effectively across functions, from data scientists and engineers to product managers and business stakeholders.

Beamery is for Everybody. Diversity and open expression are fundamental to us. We acknowledge the challenges in our industry and strive to develop an inclusive culture where everybody can contribute. We are dedicated to creating an inclusive environment for everyone, regardless of ethnicity, religion, color, sexual orientation, gender identity, race, national origin, age, disability status, or caregiver status. If, for whatever reason, you need us to make reasonable adjustments and adaptations to our recruitment process, please email [e-mail]

Visit our Diversity, Equality and Inclusion page to learn more about progress and commitments.