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- 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.
- 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 required.
- Other info: Opportunity to mentor junior engineers and shape engineering best practices.
The predicted salary is between 48000 - 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
Contact Detail:
Understanding Recruitment Recruiting Team
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 from other candidates.
✨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 highlighting any mentoring or guiding roles you've had in previous positions. This is crucial as the role involves guiding junior team members and improving engineering best practices.
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, machine learning frameworks, and cloud architecture. Emphasise any projects where you've deployed AI models or worked with LLMs, as this will resonate with the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and your hands-on experience in building production-grade features. Mention specific technologies you’ve used, like FastAPI or HuggingFace, and how they relate to the role.
Showcase Relevant Projects: If you have a portfolio or GitHub repository, include links to projects that demonstrate your skills in ML/AI, especially those involving NLP tasks or cloud deployments. This gives the hiring team tangible evidence of your capabilities.
Highlight Leadership Experience: Since the role involves guiding junior team members, be sure to mention any previous leadership or mentoring roles you've had. Discuss how you’ve improved engineering practices in past positions to show your readiness for this responsibility.
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. Bring examples of past projects where you've deployed AI models or optimised NLP tasks, as this will demonstrate your hands-on expertise.
✨Understand the Company’s AI Vision
Research the company’s current AI initiatives and be ready to discuss how your skills align with their goals. This shows that you’re not just interested in the role, but also in contributing to their mission.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities. Practice explaining your thought process clearly, especially when discussing complex topics like LLM deployments or RAG pipelines.
✨Demonstrate Leadership and Mentorship
Since the role involves guiding junior team members, be ready to share experiences where you’ve led a project or mentored others. Highlight your approach to improving engineering best practices within a team.
