Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join us as a Machine Learning Engineer to develop cutting-edge AI solutions and systems.
- Company: Be part of an innovative market leader transforming digital interactions with next-gen technology.
- Benefits: Enjoy a competitive salary, benefits package, and the chance to work in a dynamic environment.
- Why this job: Shape the future of AI while working on exciting projects that make a real impact.
- Qualifications: 3-5+ years in machine learning, full-stack experience, and proficiency in Python and AWS required.
- Other info: This role is office-based in Leicestershire, perfect for those eager to collaborate and innovate.
The predicted salary is between 43200 - 72000 £ per year.
An exceptional opportunity for a Machine Learning Engineer (with Full-Stack experience) to join an innovative market leader at the forefront of developing next-generation solutions that transform digital interactions. The role will focus on projects to leverage state-of-the-art generative AI, retrieval-augmented generation (RAG), and reasoning frameworks to build intelligent and context-aware systems.
We are seeking talented Machine Learning Engineers with full-stack software development experience to join our client's team and help shape the future of AI-powered automation. Within this dynamic role varied duties will include:
- Search relevancy engineering.
- Conversational AI Development: Design, train, fine-tune, and deploy LLMs with reasoning capabilities.
- Retrieval-Augmented Generation (RAG): Implement, optimise, and scale RAG pipelines for effective information retrieval from structured and unstructured sources.
- Model Fine-Tuning & Training: Train domain-specific models using techniques like LoRA, QLoRA, PEFT, reinforcement learning, and supervised fine-tuning (SFT).
- Model Deployment & Inferencing: Optimise model serving and inference using vLLM, DeepSpeed, TensorRT, Triton, and other acceleration frameworks.
- Multi-Agent Systems: Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy.
- AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS.
- End-to-End AI Product Development: Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring.
- Full-Stack Integration: Develop APIs and integrate ML models into web applications using FastAPI, Flask, React, TypeScript, and Node.js.
- Vector Databases & Search: Implement embeddings and retrieval mechanisms using Pinecone, Weaviate, FAISS, Milvus, ChromaDB, or OpenSearch.
Required skills & experience:
- 3-5+ years in machine learning and software development
- Proficient in Python, PyTorch or TensorFlow or Hugging Face Transformers
- Experience with RAG, LLM fine-tuning, and expertise in AWS and cloud-native AI deployments.
- Full-stack experience (React, TypeScript, Node.js) and API development.
- Familiarity with vector search and multi-agent orchestration.
Apply now to join this high growth and award-winning organisation with the opportunity to be part of building the future of AI driven projects and solutions. The role offers a highly competitive salary and benefits package and will be office based in Leicestershire.
Machine Learning Engineer employer: The Portfolio Group
Contact Detail:
The Portfolio Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in generative AI and retrieval-augmented generation (RAG). Being able to discuss recent developments or projects you've worked on in these areas during your interview will demonstrate your passion and expertise.
✨Tip Number 2
Showcase your full-stack development skills by preparing examples of past projects where you integrated machine learning models into web applications. Highlighting your experience with frameworks like FastAPI, Flask, and React can set you apart from other candidates.
✨Tip Number 3
Brush up on your knowledge of AWS services relevant to machine learning, such as SageMaker and Lambda. Being able to articulate how you've used these tools in previous roles will demonstrate your readiness for the cloud-native aspects of the job.
✨Tip Number 4
Prepare to discuss your experience with model fine-tuning and deployment techniques. Be ready to explain specific methods you've used, such as LoRA or reinforcement learning, and how they contributed to the success of your projects.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning and full-stack development. Emphasise your proficiency in Python, PyTorch, TensorFlow, and any relevant projects that showcase your skills in RAG and LLM fine-tuning.
Craft a Compelling Cover Letter: Write a cover letter that specifically addresses the job description. Mention your experience with AWS, cloud-native AI deployments, and your familiarity with vector databases. Show enthusiasm for the role and how you can contribute to the company's innovative projects.
Showcase Relevant Projects: Include a portfolio or a section in your CV that showcases relevant projects you've worked on. Highlight any experience with conversational AI, model deployment, and full-stack integration, as these are key aspects of the role.
Proofread and Edit: Before submitting your application, carefully proofread your documents. Check for any grammatical errors or typos, and ensure that all information is clear and concise. A polished application reflects your attention to detail.
How to prepare for a job interview at The Portfolio Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning frameworks like PyTorch or TensorFlow. Highlight specific projects where you've implemented RAG or fine-tuned LLMs, as this will demonstrate your hands-on expertise.
✨Demonstrate Full-Stack Knowledge
Since the role requires full-stack experience, be ready to talk about your work with React, TypeScript, and Node.js. Share examples of how you've integrated ML models into web applications, as this will show your versatility.
✨Understand the Company’s Vision
Research the company’s current projects and their approach to AI-powered automation. Being able to discuss how your skills align with their goals will make a strong impression and show your genuine interest in the role.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities. Practice explaining your thought process when tackling challenges related to model deployment or optimising ML pipelines, as this will showcase your analytical skills.
