idpp | Lead Full Stack Engineer

idpp
East London
3 months ago
Applications closed

Have you been a founding/lead Full Stack Engineer in an exciting start-up / scale up?Does working for a heavily backed, forward thinking AI company in London excite you?Are you looking to help scale and deliver new features that delight users?If so, read on…This is a full-time, on-site role, requiring five days per week in our London office.Salary: £100,000 - £120,000, based on experienceBenefits include Company equityThe client Leveraging next-generation artificial intelligence, they deliver transformative insights and seamless user experiences, setting a new benchmark for the industry.As they experience rapid growth, this client is looking for a Senior Fullstack Engineer to help scale and deliver new features that delight users.The Team You'll Be JoiningThe team is comprised of experienced leaders and engineers from top-tier companies and research institutions, bringing deep expertise in AI, machine learning, and software development. Backed by leading venture capital firms, we are a revenue-generating start-up with strong financial backing and years of runway.Joining this team means tackling exciting technical challenges at the intersection of user experience, machine learning, and infrastructure, all within a fast-paced, collaborative environment that values learning and excellence.Your RoleAs a Senior Fullstack Engineer, you’ll play a pivotal role in building and optimizing systems to meet growing user demand. Your responsibilities will include:Designing and implementing backend APIs while collaborating with the edge-computing team.Creating user-facing front-end interfaces in partnership with the product team.Ensuring the system is scalable, reliable, and has robust observability.Delivering high-quality features with thorough testing and debugging.What We’re Looking ForWe’re seeking a highly motivated engineer with:3+ years of industry experience, building scalable systems.Strong knowledge of backend technologies, particularly Python or Go.Experience working with databases such as Postgres and Redis.Proficiency in front-end technologies, including Typescript, react-query, React, and modern build tools.Bonus Skills (helpful but not essential):Familiarity with infrastructure-as-code solutions (e.g., Pulumi on AWS).Experience with mobile development (e.g., React Native).Exposure to platform engineering, C++, or video streaming technologies.What We OfferCompetitive salary: £100,000 - £120,000, based on experience.Equity in a fast-growing, innovative company.100% employer-paid private dental and vision insurance.Join in redefining what’s possible with AI-powered systems. Apply today!

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Careers

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Careers

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Careers

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.