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Machine Learning Engineer (Mid-Senior, Remote)
Job summary
A leading AI software company in Leigh is seeking a mid-senior Machine Learning Engineer to design, build, and scale ML systems. You will be responsible for developing LLM-powered conversational agents and optimizing computer vision models. The ideal candidate has over 4 years of experience in machine learning, strong Python skills, and familiarity with MLOps practices. This role offers competitive compensation and a remote-friendly, flexible work environment.
Benefits
Qualifications
- 4+ years experience writing production ready code for machine learning systems.
- Experience developing conversational AI and LLM-based products.
- Familiarity with orchestration frameworks.
- Strong exposure to MLOps practices.
Responsibilities
- Train, evaluate and deploy agentic AI systems.
- Collaborate with product and engineering teams.
- Develop production-quality machine learning frameworks.
- Conduct research on the latest AI advancements.
Skills
Education
Tools
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.
W e’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 modelsthat power real customer interactions.
- 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, conductresearch, 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 withRAG 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 systemsExperience 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
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.