At a Glance
- Tasks: Design and deploy AI-driven systems to solve real-world problems.
- Company: High-growth tech company transforming data interaction with AI.
- Benefits: Competitive salary, bonus, equity, and flexible hybrid working.
- Other info: Opportunity for high ownership and career growth in a dynamic environment.
- Why this job: Join a fast-moving team and shape the future of AI products.
- Qualifications: 4+ years in software engineering or AI, strong Python skills.
The predicted salary is between 90000 - 120000 € per year.
Join a high-growth, product-led technology company in London that is building next‑AI‑powered tools to transform how professionals interact with complex data and documents. With significant recent investment and rapid expansion plans, the team is developing cutting‑edge AI systems that automate traditionally manual, time‑intensive workflows, enabling faster, more accurate decision‑making at scale. This is a unique opportunity to work at the forefront of applied AI, leveraging the latest advancements in large models and agent‑based systems in real‑world production environments.
The Role
- Design, build, and deploy AI‑driven systems and features using state‑of‑the‑art large models.
- Develop end‑to‑end ML pipelines, from data ingestion through to production deployment and monitoring.
- Work closely with cross‑functional teams to translate complex, real‑world problems into scalable AI solutions.
- Contribute to the design of advanced architectures, including retrieval‑augmented (RAG) and multi‑agent systems.
- Optimise system performance, reliability, and scalability in production environments.
- Play a key role in technical decision‑making and overall AI strategy.
Key Skills & Experience
- 4+ years’ experience in software engineering, machine learning, or AI‑focused roles.
- Strong programming skills in Python, with experience building production‑grade systems.
- Hands‑on experience with large models and modern ML frameworks.
- Experience deploying and maintaining systems in production (MLOps, CI/CD, Docker, Kubernetes).
- Strong understanding of system design, APIs, and scalable architectures.
- Experience with cloud platforms such as AWS, GCP, or Azure.
Desirable Experience
- Experience working with LLMs in production environments.
- Exposure to agent‑based systems or advanced prompt engineering techniques.
- Experience building distributed systems or high‑performance APIs.
- Familiarity with observability and monitoring tools.
- Experience working in fast‑paced, product‑driven environments.
What’s in It for You
- Work on cutting‑edge AI systems solving complex, real‑world problems.
- High level of ownership and autonomy within a fast‑moving engineering team.
- Competitive salary of £90,000–£120,000, plus bonus and equity.
- Flexible hybrid working with a London‑based office.
- Opportunity to shape the direction of AI products from an early stage.
Interested in learning more? Apply now or reach out directly for a confidential discussion about this and similar opportunities.
Senior AI/ML Engineer in London employer: Energy Jobline CVL
Join a dynamic and innovative technology company in London that prioritises employee growth and offers a collaborative work culture. With competitive salaries, flexible hybrid working arrangements, and the chance to work on groundbreaking AI projects, this role provides an exceptional opportunity for professionals looking to make a significant impact in the field of AI and machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI/ML Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. 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 AI/ML projects, especially those that highlight your experience with large models and production systems. This will give you an edge and demonstrate your hands-on expertise.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding system design principles. Practice common ML problems and be ready to discuss your past projects in detail—this is where we can really shine!
✨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, it shows you’re genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Senior AI/ML Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior AI/ML Engineer role. Highlight your experience with large models, MLOps, and any relevant projects that showcase your skills in Python and system design.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with our mission at StudySmarter. Be specific about what excites you about the role.
Showcase Your Projects:If you've worked on any interesting AI or ML projects, make sure to mention them! Whether it's a personal project or something from a previous job, we love to see practical applications of your skills.
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!
How to prepare for a job interview at Energy Jobline CVL
✨Know Your AI Stuff
Make sure you brush up on the latest advancements in AI and machine learning, especially around large models and agent-based systems. Be ready to discuss your hands-on experience with these technologies and how you've applied them in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare examples of complex problems you've tackled using AI solutions. Think about how you translated real-world challenges into scalable systems and be ready to explain your thought process during the interview.
✨Familiarise Yourself with MLOps
Since this role involves deploying and maintaining systems in production, make sure you understand MLOps practices, CI/CD pipelines, and tools like Docker and Kubernetes. Being able to discuss your experience with these will show you're ready for the technical demands of the job.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's AI strategy, team dynamics, and future projects. This not only shows your interest but also helps you gauge if the company is the right fit for you.
