At a Glance
- Tasks: Design and implement full-stack AI systems, from FastAPI endpoints to robust training pipelines.
- Company: Join a cutting-edge tech company focused on AI innovation and infrastructure.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with excellent career advancement opportunities.
- Why this job: Make a real impact by building production-grade AI systems that integrate seamlessly into our backend.
- Qualifications: Experience in AI engineering, FastAPI, and strong problem-solving skills required.
The predicted salary is between 60000 - 80000 £ per year.
Your Opportunity
- Build production AI systems: Design and implement the full stack, from FastAPI endpoints that handle requests, to training pipelines that process data, to inference services that serve predictions. You'll own the architecture, not just the model weights.
- Train and deploy our DSLM: Fine-tune models using Unsloth/Axolotl, but more importantly, build the robust infrastructure around it - data pipelines that feed training, evaluation frameworks that catch regressions, deployment systems that handle failover. Make it production-grade.
- Integrate ML into our backend: We use FastAPI, PydanticAI, FastMCP, Memgraph. You'll extend these systems with ML capabilities, not as a separate 'ML service' but as a natural part of our backend architecture. Clean abstractions, proper error handling, observability.
- Own inference performance: Get models running fast, whether that's vLLM deployment, quantization strategies, batching optimizations, or caching.
Senior Production AI Engineer — FastAPI & LLM Infra employer: Kallikor
Join a forward-thinking company that prioritises innovation and collaboration, where as a Senior Production AI Engineer, you'll have the opportunity to shape cutting-edge AI systems in a dynamic environment. Our culture fosters continuous learning and professional growth, offering access to the latest technologies and methodologies, while our commitment to work-life balance ensures a fulfilling experience in a vibrant location. With a focus on meaningful projects and a supportive team, we empower you to make a real impact in the world of AI.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Production AI Engineer — FastAPI & LLM Infra
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving FastAPI and AI systems. We love seeing real-world applications of your work, so make sure to highlight your best stuff!
✨Tip Number 3
Prepare for interviews by practising common technical questions related to AI and production systems. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨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 candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior Production AI Engineer — FastAPI & LLM Infra
Some tips for your application 🫡
Show Your Passion for AI:When you're writing your application, let your enthusiasm for AI and production systems shine through. We want to see that you’re not just ticking boxes but genuinely excited about building robust AI infrastructures.
Tailor Your Experience:Make sure to highlight your relevant experience with FastAPI, ML integration, and data pipelines. We love seeing how your past projects align with what we do, so don’t hold back on the details!
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon overload and focus on communicating your skills and experiences effectively.
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 the role. Plus, it’s super easy!
How to prepare for a job interview at Kallikor
✨Know Your Tech Stack
Familiarise yourself with FastAPI, PydanticAI, and the other technologies mentioned in the job description. Be ready to discuss how you've used these tools in past projects and how they can be integrated into a production AI system.
✨Showcase Your Problem-Solving Skills
Prepare examples of challenges you've faced in building AI systems, particularly around model deployment and infrastructure. Highlight your approach to overcoming these issues, focusing on clean abstractions and error handling.
✨Demonstrate Your Understanding of Performance Optimisation
Be prepared to talk about strategies for improving inference performance. Discuss your experience with quantization, batching, and caching, and how these techniques can enhance the efficiency of AI models in production.
✨Ask Insightful Questions
Engage your interviewers by asking questions that show your interest in their current projects and challenges. Inquire about their existing infrastructure and how they envision integrating ML capabilities into their backend systems.
