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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 are essential.
- Other info: Mentorship opportunities available for junior engineers to enhance their skills.
The predicted salary is between 48000 - 84000 £ 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, ML/AI frameworks, and cloud architecture. Use specific examples of projects where you've deployed LLMs 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 generative AI features and your approach to improving engineering best practices.
Showcase Relevant Projects: Include a portfolio or links to projects that showcase your work in deploying AI models, especially in containerised environments. Highlight any contributions to open-source projects or personal initiatives related to ML.
Highlight Collaboration Skills: Since the role involves guiding junior team members and collaborating on scalable architecture, emphasise your teamwork experiences. Provide examples of how you've successfully worked in teams to achieve project goals.
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 help you stand out as a candidate who fits well within their team.
