Senior Software Engineer in Product

Story Terrace Inc.
London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Software Engineer (GO/PHP)

Lead / Senior Software Engineer - ML/AI

Software Engineer

Senior MLOps Engineer

Software Engineer

Senior/Staff Machine Learning Engineer

Senior Software Engineer (Python/AWS/Microservices)

Salary: £60,000 - 90,000

Hybrid working, London office - 3 days a week

Are you a passionate engineer who understands what makes products exceptional?

Do you see your role as much more than picking up tickets and writing code?

Are you excited about working with cross-functional teams, contributing to design and strategy whilst solving big, ambiguous challenges that can improve the lives of millions of people?

If so, you could be a great candidate for Product Engineer at Travtus.

About Us

Our mission is to transform the Multifamily real estate industry by empowering organisations with advanced AI solutions to drive optimisation and efficiency. Through every conversation our users have, we learn, extracting and generating vast quantities of data. This conversational data is invaluable to our clients, helping them gain insight into their customer experience, operational processes and more. Our goal is to help them use this data to make better decisions.

About the Role

As a Senior Software Engineer in Product at Travtus you will work on building the platform that enables the automation of an industry. The core services allow our solutions to communicate with third-party APIs in a reliable and scalable manner. Youre familiar with Python and backend frameworks, SOA and microservices. You have been developing scalable software products for several years and have a passion for your craft, writing great code.

You should love shipping to customers. Nothing we build matters if it isn’t solving problems for our customers and you love learning. Engineering is ever-changing. You enjoy exploring areas that you might not have experience with yet. You will be keen on developing clean and maintainable code and mentoring other developers to achieve the same. Most of all, you will enjoy working with a great team and be passionate about the work you do.

Responsibilities

  • Python Development: Deliver projects in Python, ensuring high performance and scalability
  • Deep collaboration: Work with cross-functional teams to align on goals and deliver results
  • Generative AI & ML: Integrate Gen AI solutions and explore machine learning for business applications
  • System Architecture: Design scalable, secure platform-based architectures (microservices, event-driven, etc)
  • Large-Scale Data Handling: Build systems to manage and process large data volumes efficiently
  • API Development: Design secure, scalable APIs
  • AWS Cloud Expertise: Architect and deploy systems using AWS services (Lambda, API Gateway, S3, etc)

Experience

As a Senior Software Engineer in Product at Travtus you will design, implement and improve our backend infrastructure. We are particularly interested in hearing from Engineers who have designed secure backend platform-based systems and have an excellent knowledge of modern cloud architectures, particularly AWS.

Must-have experience

  • Extensive Python experience architecting products, platforms or microservices
  • Strong product-based focus, owning components/features end to end
  • Broad architecture exposure, including microservices, event-driven and monolithic environments
  • Experience with API development
  • Hands-on experience with AWS cloud services
  • Excited to work with AI tools

Nice to have experience

  • Experience or strong interest in AI
  • Experience with TDD and an understanding of Contract testing
  • Experience with CI/CD pipelines and strategies

Compensation & benefits

  • Salary range: £60,000 - £80,000 (experience dependent)
  • Deliveroo weekly allowance
  • Healthcare
  • Central London office- 3 days a week
  • Unlimited holidays & Flexible working

About the Team

We are a passionate and collaborative team, constantly pushing boundaries to create groundbreaking solutions for our customers. Working together in person fuels our best ideas and innovations, which is why all team members spend at least three days a week in our London office.

Apply nowand help us shape the future of AI technology!

J-18808-Ljbffr

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.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.