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For Companies At a Glance
- Tasks: Design, build, and scale intelligent systems to solve real-world problems.
- Company: Join a rapidly growing, VC-backed start-up in Central London making waves in AI.
- Benefits: Enjoy a competitive salary, equity options, and flexible work arrangements.
- Why this job: Be part of a high-impact team shaping the future of AI-driven products.
- Qualifications: 2+ years in applied Machine Learning with strong Python skills required.
- Other info: Work closely with an exceptional founding team in a fast-paced environment.
The predicted salary is between 54000 - 126000 £ per year.
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SR2 | Socially Responsible Recruitment | Certified B Corporation provided pay range
This range is provided by SR2 | Socially Responsible Recruitment | Certified B Corporation. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
Direct message the job poster from SR2 | Socially Responsible Recruitment | Certified B Corporation
Machine Learning Engineer | VC-Backed Start-Up | Central London | 1 Day Onsite | Up to £90,000 + Equity
I’m working exclusively with a rapidly growing, VC-backed start-up in Central London that’s changing the game. They\’re now looking to bring in a Machine Learning Engineer to be part of their small but mighty technical team as they scale their AI-driven product offering.
This is a opportunity to get in early at a high-impact company, work closely with an exceptional founding team, and help shape the future of a platform that’s already gaining strong traction.
The Role
As a Machine Learning Engineer, you\’ll take ownership of designing, building, and scaling intelligent systems that solve real-world problems. This is not a role where you’ll just tweak models — you’ll be embedded in end-to-end product thinking: from concept to deployment.
Your work will involve:
- Developing, training, and deploying ML models (NLP, recommendation systems, or predictive analytics, depending on product focus)
- Working closely with Product and Engineering to productionise your work
- Applying deep learning, traditional ML, and MLOps best practices
- Collaborating on data strategy and architecture in a fast-moving environment
- 2+ years\’ experience in applied Machine Learning
- Strong Python skills, with familiarity in libraries like PyTorch, TensorFlow, scikit-learn
- Experience deploying models into production environments
- Solid grasp of MLOps or data pipelines (e.g., MLflow, Airflow, or similar tools)
- Previous experience in a start-up or high-growth environment a plus
- Strong communication skills – you’ll be part of strategic product discussions
The Set-Up
- Central London office (1 day a week in the office)
- Up to £90,000 base salary (DOE)
- Meaningful equity on offer – they want you to grow with them
- Backed by top-tier investors with a track record of scaling successful tech companies
- Opportunity to shape and scale AI-first products from the ground up
Seniority level
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Seniority level
Mid-Senior level
Employment type
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Employment type
Full-time
Job function
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Job function
Information Technology
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Industries
Software Development
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Machine Learning Engineer employer: SR2 | Socially Responsible Recruitment | Certified B Corporation™
Contact Detail:
SR2 | Socially Responsible Recruitment | Certified B Corporation™ Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network with professionals in the AI and machine learning space. Attend meetups, webinars, or conferences where you can connect with industry experts and potential colleagues. This can help you gain insights into the company culture and possibly get a referral.
✨Tip Number 2
Showcase your projects on platforms like GitHub or personal websites. Highlight any machine learning models you've developed, especially those that demonstrate your skills in NLP, recommendation systems, or predictive analytics. This will give you an edge by providing tangible evidence of your capabilities.
✨Tip Number 3
Prepare to discuss your experience with MLOps and data pipelines during interviews. Be ready to explain how you've deployed models into production and the tools you've used, such as MLflow or Airflow. This will show your practical knowledge and readiness for the role.
✨Tip Number 4
Research the start-up's product and its market position. Understand their AI-driven offerings and think about how you can contribute to their growth. Being able to discuss their products and your ideas for improvement will demonstrate your genuine interest and proactive mindset.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly any projects involving NLP, recommendation systems, or predictive analytics. Use specific examples to demonstrate your skills with Python and libraries like PyTorch or TensorFlow.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with their mission and the specific responsibilities of the Machine Learning Engineer position. Mention your experience in high-growth environments and your ability to collaborate effectively.
Showcase Your Projects: If you have worked on relevant projects, consider including a portfolio or links to your GitHub. Highlight any models you've developed, trained, and deployed, especially those that demonstrate your understanding of MLOps and data pipelines.
Prepare for Technical Questions: Anticipate technical questions related to machine learning concepts, model deployment, and data strategy. Be ready to discuss your previous experiences in detail, as well as your approach to problem-solving in a fast-paced environment.
How to prepare for a job interview at SR2 | Socially Responsible Recruitment | Certified B Corporation™
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and relevant libraries like PyTorch, TensorFlow, and scikit-learn. Bring examples of projects where you've developed, trained, and deployed ML models, especially in areas like NLP or recommendation systems.
✨Understand the Company’s Product
Research the start-up's AI-driven product offerings and be ready to discuss how your skills can contribute to their goals. Understanding their product will help you engage in meaningful conversations during the interview.
✨Demonstrate MLOps Knowledge
Familiarise yourself with MLOps best practices and tools such as MLflow or Airflow. Be ready to explain how you’ve applied these in previous roles, as this is crucial for the position.
✨Prepare for Collaborative Discussions
Since the role involves working closely with Product and Engineering teams, practice articulating your ideas clearly. Highlight your communication skills and any past experiences where collaboration led to successful outcomes.
