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- Tasks: Join a small team to engineer cutting-edge AI and data solutions for video meetings.
- Company: Jugo transforms digital meetings into impactful experiences with AI-powered technology.
- Benefits: Enjoy remote work flexibility with quarterly meet-ups in Bristol and a dynamic start-up culture.
- Why this job: Be part of a mission to revolutionise digital communication and enhance brand presence.
- Qualifications: Experience in back-end or full stack development, with skills in TypeScript and AWS DevOps.
- Other info: No front-end design required; adaptability and creativity are key in this fast-paced environment.
The predicted salary is between 43200 - 64800 £ per year.
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Role: Senior Multi-Modal AI and Data Engineer
Location: Remote (quarterly in-person meetings at Bristol HQ)
Duration: 6 months
Jugo is the evolution of digital meeting spaces — a powerful layer that transforms standard video calls into high-impact, high-conversion moments. As virtual becomes the norm for over 80% of business interactions, Jugo is the lever that strengthens brand presence and drives conversion in every key moment.
It integrates seamlessly over the tools you already use — like Zoom or Teams — and gives hosts the power to truly own the room.
We’re an AI-powered real-time video processing platform that turns every meeting into a high-end 3D virtual production that boosts the impact of both the host and their content. We describe it as ‘Meeting Impact Technology’ – built for customer-facing teams, marketers, and leaders who need to deliver with presence, precision, and persuasion. With cinematic visuals, intelligent flows, and AI-guided control, Jugo helps any host look remarkable, feel unstoppable, and convert more.
Our Vision: To inspire confidence in every individual by reimagining digital communication.
Our Mission: To bring unforgettable experiences to every digital presentation, so any host
can turn their brand, products, and themselves into superstars.
Our Promise: Look remarkable. Feel unstoppable. Deliver with impact. Own the Moment
Our tech stack: Jugo is a highly optimised AI and low-latency video layer that sits on top of Zoom or Teams. Our containerised GPU workloads are run on multiple clouds with serverless orchestration on AWS.
The Role:
Jugo is seeking a senior multi-modal AI and data engineer to join its small senior engineering team.
The role involves almost every form of AI, including computer vision, generative image / video, model training, low latency transcription, semantic search and prompt engineering. The role also includes a significant amount of ‘conventional’ data engineering, inc. PartiQL queries to bridge usage and billing data with external systems.
We’re a small team, so the successful candidate would be responsible for end-to-end ownership of certain microservices and workers, including the necessary ‘wiring’. As such, a general back-end or full stack background is essential (inc TS code and AWS DevOps), with C++ software engineering a bonus. Please note, no front-end design or development is required within this role.
Adaptability, speed and creative pragmatism is essential. Experience of working in a fast-paced start-up is a bonus.
Example Responsibilities:
Low latency segmentation of PowerPoint slide elements
- Low-latency slide segmentation (identifying text, background, charts, images, etc.), e.g. via fine-tuned YOLO, plus in-painting for real-time layer separation
Low-latency 2D to 3D image conversion
- Low-latency creation of 3D assets from static images
Ownership of the Data Integration Service
- Developing a data integration microservice responsible for inbound and outbound data integration including writing and testing PartiQL (or AWS SDK) queries to generate data for business-as-usual invoicing, financial and commercial system integrations
Ownership of the Business Intelligence Service
- Building a business intelligence service back-end capable of executing PartiQL queries on DynamoDB data, plus a natural language layer (e.g. via Amazon Q), returning results and adding tags to user/org tables in DynamoDB
Spatially-constrained and movement-constrained video-to-video generation
- PoC and viability testing for prompt-based video alteration while preserving camera movement and spatial elements
- Live transcription and low-latency decision making via semantic search against a pool of trigger phrases
Wide-ranging full stack engineering requests
- Assisting the team with back-end engineering tasks for the TypeScript microservices
- Using LLMs with internal data and external APIs to provide contextual, text-based user guidance
Seniority level
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Seniority level
Director
Employment type
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Employment type
Contract
Job function
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Job function
Engineering, Design, and Information Technology
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Industries
IT System Data Services, Software Development, and Climate Data and Analytics
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Senior Multi-Modal AI and Data Engineer employer: Jugo
Contact Detail:
Jugo Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Multi-Modal AI and Data Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in AI and data engineering, especially in multi-modal applications. Understanding how technologies like computer vision and generative models work will give you an edge in discussions during interviews.
✨Tip Number 2
Showcase your adaptability by discussing past experiences where you've had to pivot quickly in a fast-paced environment. Jugo values creative pragmatism, so examples of how you've solved complex problems on the fly will resonate well.
✨Tip Number 3
Network with professionals in the AI and data engineering fields, particularly those who have experience in video processing or similar technologies. Engaging with industry experts can provide insights and potentially lead to referrals.
✨Tip Number 4
Prepare to discuss your experience with AWS and serverless architectures, as these are crucial for the role. Being able to articulate your hands-on experience with cloud services will demonstrate your technical proficiency and readiness for the position.
We think you need these skills to ace Senior Multi-Modal AI and Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI, data engineering, and any specific technologies mentioned in the job description, such as PartiQL, AWS, and C++. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and data engineering. Discuss how your skills align with Jugo's mission of enhancing digital communication and provide examples of past projects that demonstrate your adaptability and creativity.
Showcase Relevant Projects: If you have worked on projects involving low-latency video processing, computer vision, or data integration, be sure to include these in your application. Highlight your role and the impact of your contributions to showcase your expertise.
Prepare for Technical Questions: Anticipate technical questions related to AI, data engineering, and the specific tools mentioned in the job description. Brush up on your knowledge of low-latency systems, semantic search, and back-end development to demonstrate your proficiency during interviews.
How to prepare for a job interview at Jugo
✨Showcase Your Technical Skills
Be prepared to discuss your experience with AI technologies, particularly in computer vision and data engineering. Highlight specific projects where you've implemented low-latency solutions or worked with PartiQL queries.
✨Demonstrate Adaptability
Since Jugo operates in a fast-paced start-up environment, share examples of how you've adapted to changing requirements or tackled unexpected challenges in previous roles.
✨Understand the Company’s Vision
Familiarise yourself with Jugo's mission to enhance digital communication. Be ready to discuss how your skills can contribute to their goal of creating impactful virtual experiences.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities. Practice explaining your thought process clearly, especially when discussing complex engineering tasks or AI model training.
