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- Tasks: Lead the development of AI features and optimise systems for real-world applications.
- Company: Join a dynamic team focused on innovative AI solutions used by thousands.
- Benefits: Enjoy remote/hybrid work options and a collaborative environment.
- Why this job: Make a real impact with cutting-edge technology while mentoring junior engineers.
- Qualifications: Expertise in Python, ML/AI, and experience with cloud environments required.
- Other info: Passion for clean code and scalable AI solutions is a must!
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
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. Contributing to open-source projects or sharing your own projects can demonstrate your expertise and passion for the field.
✨Tip Number 3
Prepare to discuss your experience with deploying AI models in cloud environments during interviews. 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 experience mentoring junior team members or leading projects. This role involves guiding others, so demonstrating your ability to collaborate and improve engineering practices is crucial.
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. Emphasise any hands-on projects or roles that involved deploying AI models or optimising NLP tasks.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and your desire to contribute to real-world applications. Mention specific technologies and frameworks listed in the job description, such as SGLang and AWS, to show your alignment with the role.
Showcase Relevant Projects: If you have worked on projects involving LLMs, RAG pipelines, or NLP automation, include these in your application. Briefly describe your role, the technologies used, and the impact of your work to demonstrate your expertise.
Highlight Leadership Experience: Since the role involves guiding junior team members, mention any previous leadership or mentoring experiences. This could be formal roles or informal situations where you helped others improve their skills or best practices.
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 ability to optimise NLP tasks or improve AI codebases. Use examples from your past work to illustrate how you approached challenges and implemented effective solutions.
✨Emphasise Collaboration and Leadership
Since the role involves guiding junior team members, be ready to discuss your experience in mentoring or leading teams. Share instances where you improved engineering best practices or collaborated on scalable projects.
✨Prepare for Cultural Fit Questions
Research the company's values and mission. Be ready to explain why you're passionate about shipping real AI features at scale and how your personal values align with theirs. This can set you apart as a candidate who fits well within their team.
