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

Nominate & Attend

Senior Software Engineer

Complexio
5 months ago
Applications closed

Related Jobs

View all jobs

Senior Software Engineer

Senior Software Engineer C# - Near Edinburgh Hybrid

Senior Software Engineer – API & ML Infrastructure

Senior Software/Data Engineering Lead

Senior C++ Software Engineer

Senior Data Engineer

Description

Complexio is Foundational AI works to automate business activities by ingesting whole company data – both structured and unstructured – and making sense of it. Using proprietary models and algorithms Complexio forms a deep understanding of how humans are interacting and using it. Automation can then replicate and improve these actions independently.

Complexio is a joint venture between Hafnia and Símbolo, in partnership with Marfin ManagementC Transport MaritimeTrans Sea Transport and BW Epic Kosan

 

About the job

As a Senior Software Engineer with broad expertise, you will be a vital part of our team, developing innovative applications that leverage AI capabilities to enhance user experiences and streamline communication. You will work alongside a talented team of Data Scientists, DevOps, Product Managers, Business Analysts experts and play a key role in designing and implementing specialised AI assistant technology.

Requirements

You have

  • Excellent problem-solving and technical skills.
  • Strong communication and collaboration skills, with the ability to work in a team.
  • Interest and experience in working on early-stage software and a wide range of tasks.
  • Proven experience using technology and how it helped you build a lasting product.

Key Responsibilities

  • Collaborate with cross-functional teams to develop key features and applications, including product managers, designers, and other engineers.
  • Design, develop, and maintain both front-end and back-end components of web applications, ensuring a seamless user experience.
  • Benchmark, analyze, and optimize web applications for scalability, security, and responsiveness.
  • Troubleshoot and resolve software defects and issues, ensuring high software quality.
  • Participate in code reviews, documentation, and the development of coding standards.

Requirements

  • Preferred M.Sc or Ph.d degree in Computer Science or a related field.
  • 7+ years of experience in Software development
  • Work experience using both compiled languages (Rust, Ocaml, Golang, Java, C#) or dynamic languages (Javascript, Python, Ruby)
  • Experience building web applications or desktop applications technologies such as Electron, tauri, React, Vue.js
  • Familiarity with CI/CD principles and technologies, including experience with GitHub Actions or similar.
  • Experience working with Relational and NoSQL databases such as Postgres, Redis, Neo4j, Milviousor MongoDB, and a good understanding of data consistency tradeoffs.
  • Proven Knowledge of cloud platforms (e.g., AWS, Azure, or GCP).

A bonus

  • Experience with graph databases such as neo4js, pinecone or milvious or similar.
  • Experience building native desktop apps.
  • Experience with NLP libraries and frameworks, such as spaCy, or Transformers.
  • Familiarity with machine learning concepts and the ability to work with NLP datase

Benefits

Remote - Must be within 2-3 hours of CET

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.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.