Hybrid AI Engineer: Scale Generative AI & ML Solutions

Hybrid AI Engineer: Scale Generative AI & ML Solutions

Full-Time 76545 - 93555 £ / year (est.) Home office (partial)
Datatech Analytics

At a Glance

  • Tasks: Design, build, and deploy innovative AI solutions at scale.
  • Company: Datatech Analytics, a leader in AI technology based in London.
  • Benefits: Competitive salary, hybrid work model, and opportunities for mentorship.
  • Other info: Join a dynamic team and influence the AI roadmap.
  • Why this job: Shape the future of AI while working with world-class datasets.
  • Qualifications: Experience in AI, ML, and strong collaboration skills required.

The predicted salary is between 76545 - 93555 £ per year.

Datatech Analytics in London is seeking an AI Engineer to design, build, and deploy innovative AI solutions at scale within a newly established AI function.

The role focuses on Generative AI, LLMs, and data capabilities across the full lifecycle from design to production.

You will work on world-class datasets, collaborate with cross-functional teams, mentor junior engineers, and shape the AI roadmap while balancing performance, security, and cost in a hybrid setup (3 days in the office).

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Hybrid AI Engineer: Scale Generative AI & ML Solutions employer: Datatech Analytics

Datatech Analytics is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration within the secure government and defence sectors. Employees benefit from meaningful projects that have a direct impact on national security, alongside opportunities for professional growth and development in cutting-edge technologies. With a hybrid working model and a focus on employee well-being, this role provides a unique chance to contribute to critical transformation programmes while enjoying a supportive and engaging workplace.

Datatech Analytics

Contact Details:

Datatech Analytics Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Hybrid AI Engineer: Scale Generative AI & ML Solutions

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Datatech Analytics or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Datatech Analytics.

Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Datatech Analytics.

Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Datatech Analytics that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Hybrid AI Engineer: Scale Generative AI & ML Solutions

Python
Communication Skills
SQL
Problem-Solving Skills
Data Engineering
Data Pipeline Development
API Integration

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Datatech Analytics.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Datatech Analytics and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Datatech Analytics

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Datatech Analytics uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.