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- Tasks: Collaborate with AI/ML scientists to develop and deploy innovative ML solutions.
- Company: Global pharmaceutical organisation transforming AI/ML in healthcare.
- Benefits: Competitive daily rate, remote work, and opportunity to work on impactful projects.
- Why this job: Join a vibrant tech ecosystem and make a real difference in the pharmaceutical industry.
- Qualifications: PhD or Master's in relevant field, strong Python skills, and ML engineering experience.
- Other info: Dynamic role with excellent opportunities for professional growth and collaboration.
The predicted salary is between 40000 - 66000 £ per year.
United Kingdom - London
Posted: 03/02/2026
Salary: £0.00 to £550.00 per Day
ID: 37088_BH
6 Months+ Contract (outside IR35)
Remote
The Role: On behalf of a global pharmaceutical organisation, I am seeking a Senior Machine Learning Engineer to help scale and operationalise AI/ML innovation. You will work at the interface of cutting-edge data science and robust engineering, partnering closely with AI/ML scientists to transition exploratory research into production-ready, repeatable ML solutions. This is an amazing opportunity to immerse yourself in a vibrant tech ecosystem while contributing to the transformation of AI/ML in the pharmaceutical industry.
Role Responsibilities:
- Partner directly with AI/ML scientists to optimise models and deploy solutions into production, acting as an internal consultant from prototype to platform.
- Translate exploratory work into robust ML pipelines, creating blueprints and best practices for scalable, repeatable machine learning.
- Explore, analyse, and visualise data to understand distributions and identify issues that may impact real-world model performance.
- Ensure data quality and model reliability through validation strategies, cleaning pipelines, and systematic testing.
- Build and improve training pipelines and reusable ML components, addressing errors and technical debt.
- Collaborate with ML Infrastructure engineers to co-develop ML platforms, strengthen MLOps capabilities, and upskill teams across the organisation.
Skills/Experience required:
- You are a technically strong, collaborative engineer with experience working alongside data scientists and life-science researchers.
- PhD or Master's degree with relevant experience, or a Bachelor's degree with strong, hands-on expertise in ML engineering.
- Experience working in a healthcare or life-science environment would be advantageous, but not essential.
- Advanced Python skills and hands-on experience with data analytics and deep learning tools such as scikit-learn, Pandas, PyTorch, Jupyter, and ML pipelines.
- Practical experience with modern data and ML tooling, including Databricks, Ray, vector databases, Kubernetes, and workflow orchestrators such as Apache Airflow, Dagster, or Astronomer.
- Experience with GPU computing, on-premise and/or in the cloud, and building end-to-end scalable ML infrastructure.
- Strong knowledge of AWS and/or Azure, containerisation, Kubernetes, automation/DevOps, and the full ML lifecycle.
- Practical expertise in data wrangling and integration of large, heterogeneous datasets relevant to drug discovery.
- Hands-on experience with large language models, including fine-tuning, DPO, training, hosting, RAG pipelines, vector databases, and multi-agent systems.
- A proven track record of building, training, and deploying production-grade ML models in industry and/or academic research.
Please apply online with your CV.
Senior Machine Learning Engineer in London employer: TechNET IT
Contact Detail:
TechNET IT Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work in AI/ML. A friendly chat can lead to insider info about job openings or even referrals that could give you an edge.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML engineering. Use platforms like GitHub to share your code and demonstrate your expertise in Python and data analytics.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and tools mentioned in the job description. Practice explaining your past projects and how they relate to the role, focusing on your collaboration with data scientists.
✨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 proactive and engaged with our platform.
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with ML pipelines, data analytics, and any relevant projects that showcase your skills in Python and deep learning tools.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI/ML in the pharmaceutical industry and how your background makes you a perfect fit for this role. Keep it engaging and personal!
Showcase Relevant Projects: If you've worked on any projects related to healthcare or life sciences, make sure to include them. Discuss the challenges you faced and how you overcame them, especially in terms of deploying ML solutions.
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. Don’t miss out!
How to prepare for a job interview at TechNET IT
✨Know Your Tech Inside Out
Make sure you’re well-versed in the tools and technologies mentioned in the job description. Brush up on your Python skills, and be ready to discuss your experience with data analytics, deep learning frameworks, and ML pipelines. Being able to talk confidently about your hands-on experience with tools like scikit-learn, PyTorch, and Databricks will definitely impress.
✨Showcase Your Collaboration Skills
Since this role involves partnering with AI/ML scientists, it’s crucial to demonstrate your collaborative spirit. Prepare examples of past projects where you worked closely with others, especially in a cross-functional team. Highlight how you’ve contributed to optimising models or deploying solutions, as this will show you can bridge the gap between research and production.
✨Prepare for Technical Questions
Expect some technical questions that test your understanding of machine learning concepts and practices. Be ready to explain your approach to building and validating ML models, as well as how you ensure data quality. Practising common interview questions related to ML lifecycle and infrastructure will help you feel more confident.
✨Demonstrate Problem-Solving Skills
Be prepared to discuss specific challenges you've faced in previous roles and how you overcame them. This could involve addressing errors in ML pipelines or improving model performance. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easier for the interviewer to follow your thought process.