Senior C++ Software Engineer 100% Remote United Kingdom

web3-resources
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Commercial Data Analyst

Consultant/Senior Consultant - Data Science Customer Data & Technology

Lead Data Engineer

Lead Data Engineer

Graduate Actuarial Analyst (Machine Learning)

Databricks Tech Lead

Join Tether and Shape the Future of Digital Finance

At Tether, we’re not just building products; we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.

About the job:

At Tether, we're committed to making advanced AI technologies more accessible. Thanks to its investment in AI infrastructure, starting from Northern Data, Tether is now in a prime position to tackle ambitious AI projects. Our goal is to build the next generation of AI models, leading innovation in AI, through an accessible, transparent, and privacy-preserving approach.

The role involves building AI solutions across the spectrum from large-scale models designed for advanced applications to smaller, highly performant models tailored for efficiency on edge devices such as mobile phones and laptops.

Our dynamic team operates entirely remotely, uniting talent from every corner of the globe. Our journey has been marked by rapid growth and efficient operations, firmly establishing us as pioneers within the industry. Join us in building AI models and solutions that not only compete with but exceed the capabilities of current leaders, driving both technological advancement and broad accessibility.

Responsibilities:

  1. Work on low-level libraries and modules in various domains.
  2. Collaborate closely with researchers to assist in coding, training, and transitioning models from research to production environments.
  3. Integrate AI features into existing products, enriching them with the latest advancements in machine learning.

Minimum Requirements:

  1. 5+ years of experienceworking with C and C++.
  2. Experience working in low-level OS / Systems / Kernel development.
  3. Demonstrated ability to rapidly assimilate new technologies and techniques.
  4. A degree in Computer Science complemented by a solid track record in development.

The average yearly salary for a Web3 C++ Developer is $200k per year, with a minimum base salary of $100k and a maximum of $280k.

#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.