At a Glance
- Tasks: Contribute to AI solutions for policing, from cloud training to real-time edge device inference.
- Company: Stealth AI startup in Greater London with a focus on innovative technology.
- Benefits: Flexible roles based on expertise and opportunities for impactful work.
- Other info: Local candidates or those willing to relocate are encouraged to apply.
- Why this job: Join a mission-driven team tackling complex engineering challenges in AI.
- Qualifications: Computer vision background and experience with vision-language models required.
The predicted salary is between 50000 - 70000 £ per year.
Stealth AI Startup in Greater London is seeking research-minded engineers to contribute to AI solutions for policing. You'll work on projects ranging from cloud training infrastructure to real-time inference on edge devices, focusing on transparency and effective policing.
Ideal candidates have a computer-vision background, experience with vision-language models, and a passion for solving complex engineering challenges. Flexibility in roles is offered based on expertise. Local candidates or those willing to relocate are encouraged to apply.
Research Engineer: Vision & Multimodal AI (Cloud & Edge) in London employer: Stealth AI Startup (Policing)
Join a pioneering Stealth AI Startup in Greater London, where innovation meets purpose in developing AI solutions for policing. Our collaborative work culture fosters creativity and flexibility, allowing you to thrive while tackling complex engineering challenges. With ample opportunities for professional growth and a commitment to transparency, we offer a unique environment that empowers you to make a meaningful impact in the field of AI.
Contact Details:
Stealth AI Startup (Policing) Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer: Vision & Multimodal AI (Cloud & Edge) in London
✨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 Stealth AI Startup (Policing) 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 Stealth AI Startup (Policing).
✨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 Stealth AI Startup (Policing).
✨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 Stealth AI Startup (Policing) 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 Research Engineer: Vision & Multimodal AI (Cloud & Edge) in London
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 Stealth AI Startup (Policing).
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Stealth AI Startup (Policing) 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 Stealth AI Startup (Policing)
✨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 Stealth AI Startup (Policing) 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.
