At a Glance
- Tasks: Develop and optimise advanced machine learning systems to solve real-world problems.
- Company: Join an innovative team transforming the industry with cutting-edge technology.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on innovation and ownership.
- Why this job: Make a real impact in a fast-paced environment while tackling complex technical challenges.
- Qualifications: MSc or PhD in relevant fields and strong Python programming skills.
The predicted salary is between 36000 - 60000 £ per year.
Do you want to help transform an industry by applying cutting-edge technology to solve meaningful, real-world problems? Join an innovative, forward-thinking team building impactful solutions in a fast-paced and collaborative environment. As a Machine Learning Engineer - Scaling, you’ll play a critical role in developing and optimising advanced machine learning systems to address complex challenges. You will work closely with cross-disciplinary teams to productionise model workflows, explore innovative methods, and contribute to scalable and efficient AI applications. This is an exciting opportunity for individuals who thrive on technical challenges, value ownership, and are motivated by innovation and impact.
Responsibilities
- Build and maintain scalable training and inference pipelines for modern AI models (e.g. Transformers, Sequence Models, etc.).
- Optimise model performance, ensuring low latency and high throughput in various operational environments.
- Design and implement reusable, modular machine learning components for internal or broader use.
- Collaborate with researchers to transition experimental code into fully operational, production-grade systems.
- Manage and enhance machine learning infrastructure—including data pipelines, distributed computing, and experiment tracking tools.
Requirements
Essential Qualifications
- MSc or PhD in fields such as Machine Learning, Computer Science, Applied Mathematics, or closely related areas.
- Strong programming expertise in Python, with proficiency in libraries like PyTorch, JAX, or TensorFlow.
- Hands-on experience developing and scaling machine learning pipelines for production environments.
- Familiarity with MLOps practices and tools such as Weights & Biases, Ray, or Docker.
- In-depth understanding of modern AI architectures, including Transformers, Diffusion Models, or similar frameworks.
- A proactive attitude, with the ability to thrive in a high-speed environment and adapt to ambiguity.
Bonus Points
- Contributions to open-source machine learning projects or tools.
- Experience in distributed training, model compression, or large-scale model serving.
- Expertise in scaling AI systems for large post-training workloads.
- Experience integrating machine learning systems into user-facing applications or APIs.
- An interest in applying machine learning in fields like biology, healthcare, or other specialised domains (prior experience not required but advantageous).
What We’re Looking For
If you are excited by complex and deeply technical challenges, enjoy working in a collaborative and fast-paced team environment, and want to make a real impact in a rapidly growing sector, this role is for you. We value innovation, ownership, and enthusiasm for tackling industry-defining problems.
Machine Learning Engineer - Scaling in London employer: BioTalent
At BioTalent, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Greater London. Our commitment to employee growth is evident through tailored development programmes and opportunities to lead impactful projects with top-tier biopharmaceutical clients, making every day a chance to drive meaningful change in the life sciences sector.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - Scaling in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow Machine Learning enthusiasts. 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 involving scalable machine learning systems. This is your chance to demonstrate your expertise in Python and libraries like PyTorch or TensorFlow.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of modern AI architectures and MLOps practices. Practice coding challenges and be ready to discuss how you've tackled complex problems in your past work.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Machine Learning Engineer - Scaling in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Machine Learning Engineer role. Highlight your programming expertise in Python and any relevant projects you've worked on, especially those involving scalable machine learning pipelines.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about machine learning and how you can contribute to our innovative team. Share specific examples of your work that demonstrate your problem-solving skills and ability to thrive in fast-paced environments.
Showcase Your Projects:If you've contributed to open-source projects or have personal projects related to machine learning, make sure to mention them! This gives us insight into your hands-on experience and your proactive attitude towards learning and innovation.
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 this exciting opportunity to join our forward-thinking team!
How to prepare for a job interview at BioTalent
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest machine learning frameworks like PyTorch, JAX, or TensorFlow. Brush up on your understanding of modern AI architectures, especially Transformers and Diffusion Models, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss any hands-on experience you have with building and scaling machine learning pipelines. Bring examples of your work, especially if you've contributed to open-source projects or developed production-grade systems. This will demonstrate your practical skills and passion for the field.
✨Emphasise Collaboration
Since this role involves working closely with cross-disciplinary teams, be ready to talk about your collaborative experiences. Share specific instances where you’ve successfully transitioned experimental code into operational systems, highlighting your ability to work well with others.
✨Be Ready for Problem-Solving
Expect to face some technical challenges during the interview. Prepare to think on your feet and showcase your problem-solving skills. Practice explaining your thought process clearly, as this will show your proactive attitude and ability to thrive in a fast-paced environment.
