Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Freelance Technical Editor

accelerate agency
Bath
9 months ago
Applications closed

Related Jobs

View all jobs

Big Data Engineer - High level Clearance (IT) / Freelance

Freelance Project Manager (AI & Machine Learning)

Online Data Analyst (Freelance)

Online Data Analyst

Online Data Analyst

Data Scientist Python Software - London (IT) / Freelance

This is a remote position


We are looking for a talented technical editor to join our thriving agency and work with an expanding portfolio of prominent SaaS brands. We need someone who understands and can confidently edit technical copy, specialising in AI-related topics. 

We pay Technical Editors between £250-420 per day, depending on experience. Working days are 7.5 hours.

About you

As our technical editor, you will be responsible for creating content outlines for our writers to follow, specifically for our technical clients. You will also be responsible for editing, proofreading, and writing content to the highest standards. You will review all content against briefs, client instructions, and specific guidelines, as well as provide constructive feedback to writers in order to improve content. 


You will also conduct research on various topics to verify accuracy, optimise content based on SEO best practices and collaborate effectively with the team in a virtual setting. Prior SEO experience is a bonus, not a requirement; we can upskill you on SEO if required.


To be a success in this role, you will need to have:


  • A strong understanding of AI concepts, including LLMs, MLops, Generative AI, and Machine Learning

  • Familiarity with AI tools and platforms

  • Strong data literacy skills, for example, understanding of datasets

  • Practical knowledge of programming is a bonus

  • Exceptional proofreading and editing skills

Qualifications
  • At least 3 years of experience creating technical content, minimum of 2 years within AI

  • A degree in a relevant field, for example, computer science or artificial intelligence

  • Extensive experience creating AI-, machine learning-, or data science-related content

  • Strong understanding of AI frameworks, algorithms, and technologies (e.g., TensorFlow, PyTorch, GPT models)

  • Awareness of emerging AI technologies and industry applications

  • Experience in building and deploying AI/ML models would be a bonus


How to Apply:

To apply and help us assess your compatibility, we ask all prospective candidates to submit their CV and availability with the role they’re applying for in the subject line – anticipating further instructions from accelerate agency. 


If you are a match for this role, we will email you to arrange a screening call. If you pass the screening call, this will be followed by a short test.


We are an equal opportunities employer and welcome applications from all different backgrounds. For us to be able to give you the best interview experience possible, please let us know in advance if you require any reasonable adjustments to the application or interview process and we will gladly see how we can accommodate them. 




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.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.