ML Engineer

Hays Technology
City of London
11 months ago
Applications closed

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Hays Software Engineering are looking for a Machine Learning Engineer to join a heavily backed, exciting Large Language Model start-up based in the US, looking to build their presence in the UK starting with an engineering hub in London. What you will be doing:Conduct research and implement solutions for the development, training, and deployment of large language models, with a focus on both pre-training and post-training processes, including fine-tuning, alignment, and optimisation.Collaborate closely with research teams to build, optimise, and maintain data sets, as well as scalable training and data pipelines for LLMs, ensuring efficient deployment in production environments.Build and maintain comprehensive documentation for infrastructure components and systems.Design and implement systems that ensure reproducibility and traceability in data preparation.Develop and maintain detailed documentation and codebases to ensure reproducibility and best practices in research and development workflows.Stay updated with advancements in machine learning, NLP, and AI, and evaluate their relevance to ongoing and future projects. What we are looking for:Master's degree in Computer Science, Machine Learning, Mathematics, or a related field, with a strong emphasis on natural language processing or machine learning.Expertise in MLOps best practices, including model versioning, CI/CD pipelines, containerisation, and cloud deployment for large-scale models.Proficient programming skills in Python, with familiarity in machine learning frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, and MLOps tools like MLflow and Kubeflow.Exceptional analytical and problem-solving abilities, with a knack for transforming complex theoretical research into practical applications.What you will get in return:Supportive Environment: Benefit from huge funding, collaborating with top-tier talent.Top-Tier Compute: Access a dedicated GPU cluster for research.Impactful Work: Shape the future of AI applications, making technology more accessible and eco-friendly.Competitive Benefits: Enjoy a competitive salary, stock options, health benefits, and more.Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be found at (url removed)

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How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.