Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the development of advanced AI models and optimise training pipelines.
- Company: Innovative tech firm at the forefront of AI technology.
- Benefits: Hybrid remote work, competitive salary, and opportunities for professional growth.
- Why this job: Join a dynamic team shaping the future of AI with real-world impact.
- Qualifications: 3-5 years in ML engineering, strong skills in PyTorch and model training.
- Other info: Collaborative environment focused on innovation and experimentation.
The predicted salary is between 48000 - 72000 £ per year.
We’re looking for an experienced Machine Learning Engineer to lead the development and training of advanced large-scale language models. In this role, you will be responsible for pushing the performance and reliability of next-generation AI systems, specifically focusing on models that assist with complex real-world tasks. You’ll work closely with cross-functional teams including infrastructure, product and research to shape both the training pipeline and the evaluation of highly capable models.
Key Responsibilities
- Design and execute large-scale training experiments on multi-GPU and distributed environments using cutting-edge ML frameworks.
- Lead both supervised fine-tuning (SFT) and reinforcement learning (RL) workflows to improve model performance on domain-specific tasks.
- Build, maintain, and optimise custom training pipelines, including dataset preparation, distributed training primitives, and scheduling of multi-node jobs.
- Collaborate across engineering and research teams to align training goals with product priorities and performance metrics.
- Troubleshoot training challenges such as stability, scaling issues, and GPU utilisation bottlenecks.
What We’re Looking For
- Experience: 3–5+ years working in ML engineering or applied machine learning roles, with hands-on responsibility for training and deploying models in production-like environments.
- Technical Skills:
- Strong proficiency with PyTorch including distributed training (e.g., DDP/FSDP).
- Practical experience training large sequence models or transformer-based architectures.
- Comfortable building and maintaining data pipelines, optimising large datasets, and handling model scaling challenges.
- Solid software engineering fundamentals — clean, maintainable code and version control best practices.
Desirable Qualities
- Experience with reinforcement learning workflows and sequence-level reward strategies.
- Familiarity with model evaluation tools and benchmarks for large-scale AI systems.
- A proactive, collaborative mindset that thrives in a fast-moving environment where innovation and experimentation are central.
Machine Learning Engineer - Hybrid Remote in City of London employer: Block MB
Contact Detail:
Block MB Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Hybrid Remote in City of London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even online forums. We can’t stress enough how important it is to build relationships; you never know who might have the inside scoop on job openings.
✨Show Off Your Skills
Don’t just tell them what you can do—show them! Create a portfolio showcasing your projects, especially those involving large-scale language models or any cool ML experiments. We love seeing practical examples of your work!
✨Ace the Interview
Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice common interview questions and maybe even do some mock interviews with friends. We want you to feel confident and ready to impress!
✨Apply Through Our Website
When you find a role that excites you, apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate candidates like you to join our team.
We think you need these skills to ace Machine Learning Engineer - Hybrid Remote in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your experience with PyTorch, distributed training, and any relevant projects you've worked on. We want to see how you fit into our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your background aligns with our goals at StudySmarter. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any interesting ML projects, make sure to mention them in your application. Whether it's a personal project or something from your previous job, we want to see your hands-on experience and creativity in action!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Block MB
✨Know Your Models Inside Out
Make sure you’re well-versed in the latest advancements in large-scale language models. Be prepared to discuss your experience with PyTorch, especially around distributed training and transformer architectures. This will show that you’re not just familiar with the theory but have practical knowledge too.
✨Showcase Your Problem-Solving Skills
Be ready to talk about specific challenges you've faced in previous roles, particularly around training stability or GPU utilisation bottlenecks. Use examples that highlight your troubleshooting skills and how you collaborated with teams to overcome these issues.
✨Demonstrate Your Collaborative Spirit
Since this role involves working closely with cross-functional teams, emphasise your communication skills. Share instances where you’ve successfully aligned technical goals with product priorities, showcasing your ability to bridge the gap between technical and non-technical stakeholders.
✨Prepare for Technical Questions
Expect in-depth technical questions related to ML frameworks and data pipelines. Brush up on your knowledge of orchestration tools like Kubernetes and Slurm, and be ready to discuss how you optimise datasets and manage multi-node jobs. This will help you stand out as a candidate who is both knowledgeable and hands-on.
