At a Glance
- Tasks: Lead the development of AI features and optimise systems for real-world applications.
- Company: Join a forward-thinking tech company transforming industries with cutting-edge AI solutions.
- Benefits: Enjoy remote/hybrid work options, competitive salary, and opportunities for professional growth.
- Other info: Opportunity to mentor junior engineers and shape engineering best practices.
- Why this job: Be part of a dynamic team making a real impact in AI technology and innovation.
- Qualifications: Expertise in Python, ML/AI, and experience with cloud environments are essential.
The predicted salary is between 43200 - 72000 £ per year.
We are looking for a seasoned ML Engineer to take a lead role in building and integrating production-grade AI and generative AI features across a platform used by thousands. This is a hands-on engineering role where you will design, deploy, and optimise systems that power real-world use cases - from LLM deployments to RAG pipelines and NLP automation.
What you will do:
- Maintain and improve AI codebases for performance and reliability
- Deploy LLMs using frameworks like SGLang, TGI, vLLM
- Build RAG pipelines, embedding, reranking, and evaluation frameworks
- Optimise NLP tasks (summarisation, classification, sentiment)
- Collaborate on scalable cloud architecture (AWS), infra design, and CI/CD
- Drive compute efficiency, cost-effectiveness, and sustainability
- Guide junior team members and improve engineering best practices
Your skillset:
- Expert Python developer (pandas, FastAPI, Pydantic)
- Strong ML/AI experience including AutoML, LLMs, HuggingFace, LangChain
- Proficiency in Linux, Git, PostgreSQL, and API development
- Experience deploying AI models in containerised, cloud-based environments
- Bonus: agentic AI (smolagents, AutoGen), fine-tuning, MLOps know-how
If you are passionate about shipping real AI features at scale and love clean code, apply now!
Senior Machine Learning Engineer employer: Understanding Recruitment
Join a forward-thinking technical consultancy that values innovation and collaboration, offering a dynamic work culture where your expertise in AWS cloud and software engineering will be recognised and rewarded. With competitive salaries, a generous benefits package including a yearly bonus and enhanced parental leave, and opportunities for professional growth, this role as Lead Cloud Engineer in locations like Surrey, Bristol, and Glasgow provides a unique chance to lead impactful projects while enjoying a healthy work-life balance.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the specific frameworks mentioned in the job description, such as SGLang and TGI. Having hands-on experience or projects showcasing your skills with these tools can set you apart during discussions.
✨Tip Number 2
Engage with the AI and ML community online, particularly on platforms like GitHub or relevant forums. Sharing your insights or contributing to open-source projects can demonstrate your expertise and passion for the field.
✨Tip Number 3
Prepare to discuss your previous experiences with deploying AI models in cloud environments. Be ready to share specific examples of how you've optimised performance and reliability in past projects.
✨Tip Number 4
Showcase your leadership skills by thinking about how you would guide junior team members. Prepare examples of how you've improved engineering practices in your previous roles, as this aligns well with the responsibilities of the position.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, ML/AI frameworks, and cloud architecture. Use specific examples of projects where you've deployed AI models or optimised NLP tasks to demonstrate your expertise.
Craft a Compelling Cover Letter:In your cover letter, express your passion for AI and how your skills align with the role. Mention any relevant experience with LLMs, RAG pipelines, and your approach to mentoring junior team members.
Showcase Your Projects:If possible, include links to your GitHub or portfolio showcasing projects related to machine learning, especially those involving deployment in cloud environments or using frameworks like HuggingFace and LangChain.
Highlight Collaboration Skills:Emphasise your ability to work in teams, particularly in collaborative environments. Mention any experience you have with CI/CD processes and how you've contributed to engineering best practices in previous roles.
How to prepare for a job interview at Understanding Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, ML frameworks, and cloud architecture. Highlight specific projects where you've deployed LLMs or built RAG pipelines, as this will demonstrate your hands-on expertise.
✨Demonstrate Problem-Solving Abilities
Expect technical questions that assess your problem-solving skills. Prepare to explain how you would optimise NLP tasks or improve AI codebases for performance and reliability, showcasing your analytical thinking.
✨Emphasise Collaboration and Leadership
Since the role involves guiding junior team members, be ready to share examples of how you've collaborated in teams or mentored others. This will show your ability to lead and improve engineering best practices.
✨Prepare Questions About the Company’s AI Vision
Research the company's current AI initiatives and be ready to ask insightful questions about their future plans. This shows your genuine interest in the role and helps you understand how you can contribute to their goals.
