At a Glance
- Tasks: Design and scale AI systems for the beauty industry, focusing on ML and computer vision.
- Company: Renude, an award-winning tech company transforming customer support in beauty with AI.
- Benefits: Competitive pay, remote work, flexible hours, and a culture of personal growth.
- Why this job: Join a dynamic team and influence cutting-edge technology in a fast-paced startup environment.
- Qualifications: 4+ years in machine learning, strong Python skills, and experience with conversational AI.
- Other info: Opportunity to work with innovative tech and make a real impact in the beauty sector.
The predicted salary is between 48000 - 72000 £ per year.
Renude builds AI-powered software for the beauty industry, helping brands deliver personalised, expertise-focused customer support through intelligent digital agents. Our technology powers e-commerce experiences including skin analysis, product recommendation and LLM-based chat. We’ve been awarded by CEW, Beauty Innovation Awards, Tech Nation and more, and have raised over $3M from leading tech investors. Our team combines tech, formulation, dermatology, e-commerce and sales expertise.
We’re looking for a mid-senior (4+ years experience) Machine Learning Engineer to help design, build, and scale our production ML systems with ownership from experimentation through to deployment. You’ll work end to end on LLM-powered conversational agents and support the training, optimisation, and deployment of computer vision models that power real customer interactions.
What We Offer:- Train, evaluate and deploy agentic AI systems and computer vision models for real-world use
- Collaborate with product and engineering to integrate ML systems into user-facing features
- Develop and deploy production-quality machine learning frameworks, while maintaining robust MLOps pipelines
- Stay up-to-date with the latest advancements in AI, conduct research, and explore innovative techniques
- Influence key decisions on architecture and implementation of scalable, reliable, and cost-effective engineering solutions
- 4+ years experience writing production ready code for machine learning systems
- 2+ years experience developing conversational AI, RAG, agentic systems or LLM-based products
- Familiarity with RAG orchestration frameworks such as LangChain or LlamaIndex
- 2+ Experience with production optimisation for RAG systems, including latency, token cost control, context window constraints, monitoring and prompt versioning
- Strong Python skills and experience with PyTorch, TensorFlow or Keras
- Exposure to MLOps practices and hands-on experience with Sagemaker and/or Vertex AI
- Bachelor's degree in a technical field such as computer science or years of equivalent experience
- Comfortable working autonomously and taking ownership in a fast-moving, remote, startup environment
- Masters or advanced degree in artificial intelligence, machine learning, natural language processing, computer vision, or related field
- 2+ years experience training and optimising computer vision models
- Proficiency working with vector stores, data chunking, embeddings, retrieval, ranking and recommendation systems
- Experience with Django or similar Python web frameworks
- Familiarity with Docker and containerised development
- Exposure to CI/CD pipelines and infrastructure-as-code
- Competitive compensation (based on experience and location)
- Remote-friendly culture with flexible working hours
- Opportunity to work with cutting edge technologies
- High ownership and real technical influence
- A supportive team that values product excellence and personal growth
Machine Learning Engineer (Mid-Senior, Remote) in Kingston upon Hull employer: Renude
Contact Detail:
Renude Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (Mid-Senior, Remote) in Kingston upon Hull
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and AI. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and coding challenges. Practice explaining your past projects and how they relate to the role at Renude. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Machine Learning Engineer (Mid-Senior, Remote) in Kingston upon Hull
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning systems and conversational AI. We want to see how your skills align with what we're looking for, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're excited about working with AI in the beauty industry and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any cool ML projects, especially those involving LLMs or computer vision, make sure to mention them. We love seeing real-world applications of your skills, so include links or descriptions of your work!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Renude
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals, especially around conversational AI and RAG systems. Be ready to discuss your past projects in detail, focusing on the challenges you faced and how you overcame them.
✨Showcase Your Code
Prepare to share examples of your production-ready code. If you’ve worked with frameworks like PyTorch or TensorFlow, have a project ready to demonstrate your skills. This will show that you can not only talk the talk but also walk the walk.
✨Understand Their Tech Stack
Familiarise yourself with the tools and technologies mentioned in the job description, such as LangChain, Sagemaker, and Docker. Being able to discuss how you've used similar tools in your previous roles will give you an edge.
✨Ask Smart Questions
Prepare insightful questions about their current ML systems and future projects. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you. Think about how you can contribute to their goals!