At a Glance
- Tasks: Lead the strategy for an innovative AI product, shaping the future of technology.
- Company: Established software business with a strong client base and a collaborative culture.
- Benefits: Competitive salary, strong benefits package, and flexible remote/hybrid working options.
- Other info: Join a dynamic team with opportunities for growth and technical leadership.
- Why this job: Make a real impact in a multi-billion industry by creating cutting-edge AI solutions.
- Qualifications: 4+ years in AI/ML production and 8+ years in software engineering required.
The predicted salary is between 120000 - 150000 € per year.
A technical leadership role shaping the strategy for an AI first product addressing a multi billion industry still running on PDFs and spreadsheets. The north star is creating a genuinely forward-looking AI product ecosystem, not just layering AI on legacy applications. There's meaningful work to do here and a client base won over 20 years to ship solutions to.
Your job at Staff level means you'll help set AI/ML vision, processes, and best practices genuine technical leadership, not a senior IC with a fancier title. This role leads on multi-agent systems and LLM orchestration patterns, building complex agentic workflows.
You'd be working with frameworks like LangGraph, Pydantic AI, and Agent SDK. Your background is most likely in an agile development environment where you are internal or external client facing, working collaboratively with product teams across fast moving iterations.
Technical requirements:
- 4+ years deploying AI / ML solutions into production
- 8+ years experience in Software Engineering / data science
- Expert with Python / Java
- Strong AWS, Amazon Bedrock or equivalent
- Datadog, Databricks, MLFlow
- LangGraph, LangFuse, Claude, Gemini, ChatGPT
- Terraform, Docker, K8
- RMDB, Graph, Vector DBs
- Claude Code, Github
Company: Established software business, profitable and serving 1000+ customers based in Central London.
Package / what's on offer: Salary in the region of £120K - £150K + a strong benefits package. Remote and Hybrid working set ups depending on your location.
Staff AI / ML Engineer - Hybrid / Remote in Leeds employer: SR2 | Socially Responsible Recruitment | Certified B Corporation™
Join a leading software business in Central London that champions innovation and technical leadership in the AI/ML space. With a strong focus on employee growth, you will have the opportunity to shape the future of AI products while enjoying a competitive salary and a robust benefits package. Our collaborative work culture supports hybrid and remote setups, ensuring a flexible work-life balance as you contribute to meaningful projects for a diverse client base.
Contact Detail:
SR2 | Socially Responsible Recruitment | Certified B Corporation™ Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Staff AI / ML Engineer - Hybrid / Remote in Leeds
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI/ML space and let them know you're on the lookout for opportunities. You never know who might have the inside scoop on a role that’s perfect for you.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your AI/ML projects. This is your chance to demonstrate your expertise with frameworks like LangGraph and Pydantic AI, making you stand out to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and leadership skills. Be ready to discuss how you've shaped AI/ML strategies in the past and how you can contribute to building complex agentic workflows.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some exciting roles waiting for you, and applying directly helps us see your enthusiasm and fit for the team. Let’s get you on board!
We think you need these skills to ace Staff AI / ML Engineer - Hybrid / Remote in Leeds
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with our job description. Highlight your expertise in AI/ML solutions and software engineering, and don’t forget to mention any relevant frameworks you've worked with!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how your background makes you a perfect fit for shaping our AI/ML vision. Keep it engaging and personal.
Showcase Your Projects:If you've worked on any cool projects involving multi-agent systems or LLM orchestration, make sure to include them in your application. We love seeing real-world applications of your skills!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our team!
How to prepare for a job interview at SR2 | Socially Responsible Recruitment | Certified B Corporation™
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technical requirements listed in the job description. Brush up on your Python, Java, and AWS skills, and be ready to discuss how you've deployed AI/ML solutions in production. Prepare examples that showcase your experience with frameworks like LangGraph and Databricks.
✨Showcase Your Leadership Skills
Since this is a technical leadership role, be prepared to talk about your experience in shaping AI/ML vision and processes. Think of specific instances where you’ve led teams or projects, and how you’ve influenced best practices in an agile environment. Highlight your ability to work collaboratively with product teams.
✨Understand the Business Context
This role is about more than just coding; it’s about addressing a multi-billion industry. Research the company’s client base and their needs. Be ready to discuss how you can contribute to creating a forward-looking AI product ecosystem that goes beyond just layering AI on legacy applications.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills and your approach to building complex agentic workflows. Think through potential scenarios involving multi-agent systems and LLM orchestration patterns, and be ready to explain your thought process and decision-making in those situations.
