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- Tasks: Develop and optimise AI pipelines while managing cloud infrastructure.
- Company: Join a forward-thinking tech company at the forefront of AI innovation.
- Benefits: Attractive salary, flexible working options, and opportunities for skill development.
- Why this job: Be part of groundbreaking projects that shape the future of AI technology.
- Qualifications: 2+ years in coding, expert in Python, and strong back-end skills required.
- Other info: Dynamic team environment with significant career advancement potential.
The predicted salary is between 48000 - 72000 £ per year.
Data Science operate GPUs/accelerators where needed. Stand up and harden RAG pipelines (indexing, retrieval policies, grounding, guardrails) and agent frameworks. Take basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost tuning. Participate in on-call for your area and drive root-cause analysis with crisp follow-ups.
Collaborate Pair with back-end translate business problems into shipped ML features.
- 2+ years leading while coding.
- Expert Python; strong back-end chops (e.g., FastAPI, gRPC, Postgres, pub/sub/streams).
- Agents hands-on with time-series analysis (forecasting, change-point, drift).
- Cloud GPU/accelerator experience.
- Multimodal pipelines (text + voice + screenshots).
- Prior experience in contact center/CX analytics or novelty/anomaly systems.
- Founder or founding engineer experience.
GenAI Engineer employer: Clarity
Contact Detail:
Clarity Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GenAI Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in GenAI or related fields. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, cloud infrastructure, or any cool ML features you've built. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with GPUs, RAG pipelines, and any relevant frameworks. Practice common interview questions and scenarios to boost your confidence.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to highlight your experience with cloud services and data science, and let us know why you're excited about the role!
We think you need these skills to ace GenAI Engineer
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python and any back-end technologies you've worked with. We want to see how your skills align with the role, so don’t hold back on showcasing your expertise!
Tailor Your Application: Take a moment to customise your application for the GenAI Engineer position. Mention specific projects or experiences that relate to RAG pipelines, cloud infrastructure, or time-series analysis. This helps us see how you fit into our team.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon unless it's relevant. We appreciate a well-structured application that gets straight to the point!
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 Clarity
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and cloud platforms like GCP, AWS, or Azure. Brush up on your knowledge of FastAPI, gRPC, and how to manage CI/CD pipelines. Being able to discuss these topics confidently will show that you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've translated business problems into machine learning features. Think about times when you’ve tackled complex issues, particularly in contact centre analytics or anomaly detection. This will demonstrate your ability to apply your skills in real-world scenarios.
✨Get Familiar with RAG Pipelines
Since the role involves working with RAG pipelines, make sure you understand indexing, retrieval policies, and grounding. Be ready to explain how you would harden these pipelines and implement guardrails. Showing that you can think critically about these processes will set you apart.
✨Prepare for Collaboration Questions
As collaboration is key in this role, think about your past experiences working in teams. Be prepared to discuss how you’ve paired with back-end developers and contributed to projects. Highlight your communication skills and how you ensure everyone is aligned towards a common goal.
