National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

React Native developer - AI-driven startup - London - up to 50k - 5 days a week in office.

Opus Recruitment Solutions
London
8 months ago
Applications closed

Related Jobs

View all jobs

Software Developer

Machine Learning Engineer

Senior Software Engineer – API & ML Infrastructure

Data Engineer

Lead Data Engineer

Head of Engineering

React Native developer - AI-driven startup - London - up to 50k - 5 days a week in office.


I am currently working with a fast-growing AI-driven startup revolutionizing the financial sector.


They are building innovative, scalable financial solutions leveraging artificial intelligence and machine learning to transform the way individuals manage their finances.


All of their projects that you will be working on are greenfield, providing a unique opportunity for a developer like you to make a direct impact on the development of cutting-edge fintech products.


They are looking for a talentedReact Native Developerto join their team as they continue to scale their operations.


If you are looking for an exciting opportunity to be part of a dynamic team that values creativity, autonomy, and innovation then I want to hear from you!


Responsibilities:

  • Design and build advanced applications using React Native for iOS and Android platforms.
  • Collaborate with cross-functional teams to define, design, and ship new features.
  • Work closely with backend developers to integrate RESTful APIs and other backend services.
  • Participate in the full software development lifecycle, including writing clean, maintainable, and scalable code.
  • Optimize applications for maximum speed, performance, and scalability, especially as we grow.
  • Contribute to technical discussions, architectural decisions, and mentor junior developers.
  • Ensure the quality and functionality of applications by writing unit and integration tests.
  • Stay updated with the latest industry trends and apply them to development processes.


Qualifications:

  • 3+ years of professional experience in mobile app development with React Native.
  • Proven experience working on greenfield projects, from concept to launch.
  • Strong proficiency in JavaScript, TypeScript, and modern mobile development frameworks.
  • Experience working with RESTful APIs, third-party libraries, and SDKs.
  • Solid understanding of mobile app design principles and best practices.
  • Familiarity with version control tools (e.g., Git), continuous integration, and agile methodologies.
  • Experience with deploying applications on both the App Store and Google Play.
  • Ability to work in a fast-paced, scaling environment and adapt to changing requirements.


What They Offer:

  • Competitive salary and equity options.
  • Opportunity to work on groundbreaking projects in the fintech space.
  • A dynamic and collaborative startup environment with plenty of room for growth.
  • Professional development and career progression opportunities.
  • Work with cutting-edge AI and machine learning technologies.


If you are interested in this role please share your cv

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.