At a Glance
- Tasks: Build and optimise AI workflows for visual content generation in e-commerce.
- Company: Join a dynamic team from top tech companies like Google and Amazon.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Exciting environment with potential for career advancement and learning.
- Why this job: Make a real impact on cutting-edge AI technology and help shape the future of content.
- Qualifications: Programming experience and a problem-solving mindset are essential.
The predicted salary is between 50000 - 70000 £ per year.
About SOTA
SOTA is the operating system for visual intelligence, providing a self-improving platform to ideate, produce, and optimize content across enterprises. By combining cutting-edge technology with innovative solutions, SOTA enables businesses to elevate their content strategies. Our team comes from Revolut, Meta, Google, and Amazon, and we are backed by top-tier VCs.
The role
We are looking for a technically-minded AI engineer to join our workflows team. You will build, optimise, and debug visual AI pipelines that power content generation for some of the world's largest e-commerce brands. You will not just run workflows, you will make them faster, smarter, and more reliable.
What you will do:
- Design and maintain node-based AI workflows for visual content generation
- Debug and optimise pipelines to improve quality, speed, and cost-efficiency
- Onboard enterprise customers onto the platform and tailor workflows to their brand requirements
- Identify opportunities to automate and scale outputs across customer accounts
- Work closely with the product and engineering team to improve the platform based on real workflow experience
What we are looking for:
- Some programming experience in any language. What matters is that you have written code to solve a problem or build something, whether as a hobby, at university, or on the job
- A problem-solver's mindset. You spot inefficiencies, you want to fix them, and you follow through
- Hands-on experience with node-based AI tools such as ComfyUI, n8n, or similar automation and orchestration platforms
- Genuine curiosity about how AI works, including large language models, image generation, and video, even if self-taught
Bonus points:
- Experience with prompt engineering or fine-tuning AI models
- Background in e-commerce, creative production, or enterprise software
- Scripting with Python or JavaScript to extend and automate workflows
Tech / AI Specialist Tech / AI Specialist employer: Sota
SOTA is an exceptional employer that fosters a dynamic and innovative work culture, where creativity meets cutting-edge technology. As a Tech / AI Specialist, you will have the opportunity to collaborate with a talented team from industry giants like Revolut and Google, while enjoying a supportive environment that prioritises employee growth and development. With a focus on meaningful projects that drive real impact for leading e-commerce brands, SOTA offers a unique chance to be at the forefront of visual intelligence in a rapidly evolving field.
StudySmarter Expert Advice🤫
We think this is how you could land Tech / AI Specialist Tech / AI Specialist
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Sota.
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We think you need these skills to ace Tech / AI Specialist Tech / AI Specialist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Sota, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Sota. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Sota
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Sota!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
