Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop a cutting-edge Android app to enhance in-store shopping experiences.
- Company: Join a VC-backed stealth-mode company revolutionising retail with behavioural AI solutions.
- Benefits: Enjoy a dynamic work environment with opportunities for innovation and collaboration.
- Why this job: Be part of a mission-driven team creating impactful mobile experiences in retail.
- Qualifications: Experience with real-time protocols and on-device machine learning is essential.
- Other info: Ideal for those passionate about next-gen retail and behavioural data.
The predicted salary is between 36000 - 60000 £ per year.
About Us:
We’re a VC-backed stealth-mode company building behavioural AI solutions for the retail industry. Our platform is designed from the ground up — no legacy, no patchwork systems — just a clean slate and a clear vision. Our mission is to bring the intelligence of modern machine learning directly to the in-store experience, powering real-time, context-aware interactions in physical retail environments through beautifully engineered mobile experiences.
Role:
We're looking for an experienced Android Engineer to help with the development of a cutting-edge consumer facing app designed to change the physical in-store shopping experience. You’ll collaborate closely with our team of ML & backend engineers and product to deliver a mobile experience that feels fast, personalised, and deeply responsive to user context.
Responsibilities:
- Architect and implement Android features that include:
- Real-time & bi-directional communication
- On-device inference using Edge optimised frameworks
- Offline-aware & offline-first UX flows using prefetching, caching, and background sync
Essential Qualifications:
- Experience with real-time protocols (eg. WebSockets gRPC, MQTT, SSE or similar)
- Experience with implementing on-device machine learning (eg. PyTorch Mobile, ML Kit, TensorFlow Lite)
- Strong understanding of Android performance: lifecycle, coroutines, memory, and threading
- Familiarity with edge-friendly architecture: offline-first, sync queues, reactive flows
- Comfort working in fast-paced, zero-legacy, product-driven environments
- Curiosity about behavioural data, context-aware design, or next-gen retail
Nice-to-Haves:
- Knowledge and/or Experience with Bluetooth & sensor APIs
- Knowledge and/or Experience working with USB-C connected peripheral devices
- Experience in early-stage product design and MVP development
Android Engineer employer: algo1
Contact Detail:
algo1 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Android Engineer
✨Tip Number 1
Familiarise yourself with the latest Android development tools and frameworks, especially those related to real-time communication and on-device machine learning. Being well-versed in technologies like WebSockets, gRPC, and TensorFlow Lite will give you a significant edge during discussions with our team.
✨Tip Number 2
Showcase your understanding of performance optimisation in Android apps. Be prepared to discuss specific strategies you've used to enhance app performance, such as memory management and efficient threading, as these are crucial for the role.
✨Tip Number 3
Demonstrate your ability to work collaboratively in a fast-paced environment. Share examples from your past experiences where you successfully collaborated with cross-functional teams, particularly with AI and ML engineers, to deliver impactful mobile solutions.
✨Tip Number 4
Express your curiosity about behavioural data and context-aware design. Research current trends in retail technology and be ready to discuss how these insights can influence the development of user-centric mobile experiences in your interview.
We think you need these skills to ace Android Engineer
Some tips for your application 🫡
Understand the Role: Read the job description thoroughly to grasp the specific skills and experiences required for the Android Engineer position. Highlight your relevant experience with real-time protocols and on-device machine learning in your application.
Tailor Your CV: Customise your CV to reflect the qualifications mentioned in the job description. Emphasise your experience with Android performance, offline-first UX flows, and collaboration with AI & ML teams. Use keywords from the job listing to make your application stand out.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for behavioural AI solutions and your understanding of the retail industry. Mention specific projects where you implemented real-time communication or optimised app performance, demonstrating how you can contribute to their mission.
Proofread and Submit: Before submitting your application, proofread all documents for spelling and grammatical errors. Ensure that your application is complete and that all required documents are included. Submit your application through our website to ensure it reaches the right team.
How to prepare for a job interview at algo1
✨Showcase Your Technical Skills
Be prepared to discuss your experience with real-time protocols and on-device machine learning. Bring examples of past projects where you've implemented these technologies, as this will demonstrate your capability to handle the responsibilities outlined in the job description.
✨Understand the Company’s Vision
Research the company’s mission and how they aim to revolutionise the retail industry with behavioural AI. Being able to articulate how your skills align with their goals will show your genuine interest in the role and the company.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with ML and backend engineers, think of examples where you successfully collaborated with cross-functional teams. Highlight your communication skills and how you can contribute to a cohesive team environment.
✨Demonstrate Problem-Solving Abilities
Expect technical questions that assess your problem-solving skills, especially regarding Android performance and architecture. Be ready to discuss how you would approach optimising an app for low latency and efficient memory usage.
