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- Tasks: Lead the development of AI solutions using Databricks and generative models.
- Company: Join a tech-forward company focused on real-world AI applications.
- Benefits: Enjoy competitive pay, flexibility, and opportunities for career growth.
- Why this job: Work with cutting-edge technology in a collaborative environment that values innovation.
- Qualifications: 4+ years in AI/ML engineering with strong Python and Databricks experience required.
- Other info: Ideal for those passionate about scalable AI and machine learning systems.
The predicted salary is between 48000 - 84000 £ per year.
Are you passionate about building scalable AI and machine learning systems — and fluent in all things Databricks? We’re hiring an AI Engineer to lead the development of next-gen solutions using generative AI, ML, and Databricks-native tools. This is a fantastic opportunity for a skilled engineer who wants to build real-world applications with Databricks at the heart of it all. This role is ideal for someone who enjoys blending technical precision with innovation.
You’ll:
- Build and manage ML pipelines in Databricks using MLflow, Delta Lake, Spark, and Mosaic AI.
- Train and deploy generative models (LLMs, GANs, VAEs) for NLP, content generation, and synthetic data.
- Architect scalable solutions using Azure, AWS, or GCP.
- Optimize performance and maintain model governance using Databricks-native tools.
- Collaborate with cross-functional teams and clients to deliver real-world AI applications.
Required:
- 4+ years in AI/ML engineering with hands-on Databricks experience.
- Strong Python skills with experience in TensorFlow, PyTorch, or Scikit-learn.
- Cloud experience (Azure preferred, or AWS/GCP).
- Certifications in Databricks or Azure (e.g., Databricks ML Professional).
Why Join Us?
- Work with purpose – deliver AI that solves real-world problems for major organizations.
- Tech-forward culture – thrive in a collaborative team of AI and data specialists.
- Databricks-driven innovation – work at the forefront of platform-native development.
- Career growth – gain hands-on experience with the latest in generative AI and scalable ML systems.
- Competitive package – enjoy strong compensation, flexibility, and benefits.
AI Engineer (Databricks Specialist) employer: TechYard
Contact Detail:
TechYard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer (Databricks Specialist)
✨Tip Number 1
Familiarise yourself with Databricks and its ecosystem. Since this role focuses heavily on Databricks-native tools, having a deep understanding of MLflow, Delta Lake, and Spark will set you apart from other candidates.
✨Tip Number 2
Showcase your experience with generative models. Be prepared to discuss specific projects where you've trained and deployed models like LLMs or GANs, as this will demonstrate your hands-on expertise in the field.
✨Tip Number 3
Highlight your cloud experience, especially with Azure. Since the role mentions cloud architecture, being able to articulate your experience with Azure services will be crucial in making a strong impression.
✨Tip Number 4
Network with current employees or professionals in the AI/ML space. Engaging with our team or attending relevant meetups can provide insights into our culture and expectations, which can be beneficial during interviews.
We think you need these skills to ace AI Engineer (Databricks Specialist)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI and machine learning, particularly your hands-on work with Databricks. Emphasise your skills in Python and any relevant frameworks like TensorFlow or PyTorch.
Craft a Compelling Cover Letter: In your cover letter, express your passion for building scalable AI systems and your familiarity with Databricks. Mention specific projects or experiences that demonstrate your ability to innovate and solve real-world problems.
Showcase Relevant Projects: If you have worked on projects involving generative models or ML pipelines, be sure to include these in your application. Describe your role, the technologies used, and the impact of your work.
Highlight Certifications: If you hold any certifications in Databricks or Azure, make them prominent in your application. This will help demonstrate your commitment to professional development and expertise in the required tools.
How to prepare for a job interview at TechYard
✨Showcase Your Databricks Expertise
Make sure to highlight your hands-on experience with Databricks during the interview. Be prepared to discuss specific projects where you've built ML pipelines or deployed generative models using Databricks-native tools.
✨Demonstrate Your Technical Skills
Brush up on your Python skills and be ready to talk about your experience with frameworks like TensorFlow, PyTorch, or Scikit-learn. You might be asked to solve a technical problem or explain your approach to building scalable AI solutions.
✨Understand Cloud Platforms
Since cloud experience is crucial for this role, ensure you can discuss your familiarity with Azure, AWS, or GCP. Be ready to explain how you've architected solutions in the cloud and optimised performance for AI applications.
✨Prepare for Collaborative Scenarios
This role involves working with cross-functional teams, so think of examples where you've successfully collaborated with others. Be ready to share how you communicate complex technical concepts to non-technical stakeholders.
