Want to build AI products that actually make it into production, rather than spending your time experimenting with models that never get used?
I’m working with an innovative HRTech SaaS business using AI to transform how organisations manage job architecture, skills and workforce data.
We’re looking for a hands-on Machine Learning Engineer to join their ML team and work directly with the ML Tech Lead.
This isn’t a research-only role. You’ll be building, testing and deploying real NLP and LLM features that customers actually use.
What you’ll be doing:
- Building and deploying LLM and NLP features into production
- Working with text classification, embeddings and semantic similarity
- Designing prompts, structured outputs and evaluating LLM performance
- Developing Python-based services and APIs
- Building evaluation frameworks, testing models and improving accuracy
- Working closely with engineers and product teams to turn ideas into working solutions
What we’re looking for:
- 3+ years of hands-on ML/NLP engineering experience, including production deployments
- Strong Python skills, including APIs (ideally FastAPI), testing and debugging
- Practical LLM experience, not just experimenting with ChatGPT
- Solid understanding of NLP fundamentals and model evaluation
- Experience using AI coding assistants such as Claude, Copilot or ChatGPT effectively, while being able to write, understand and debug code independently
- Someone who can explain technical decisions clearly and isn’t afraid to challenge an approach
- Experience with AWS, Docker, CI/CD or responsible AI would be a bonus.
What matters most?
We’re not looking for someone who can simply list AI tools on their CV.
We want someone who can talk us through something they’ve actually built.
What was the problem? What data did you use? How did you evaluate the results? What went wrong? How did you fix it?
And importantly, how do you use AI coding assistants to become a better engineer without becoming dependent on them?
Ideally, we’re looking for a strong Senior Engineer, but we’re absolutely open to a capable mid-level candidate with the right hands-on experience.
If you enjoy solving complex problems, building real products and working in a fast-moving SaaS environment, I’d love to hear from you.
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