At a Glance
- Tasks: Join our team to develop AI-driven video workflows using Python and cutting-edge technologies.
- Company: V-Nova, a leader in video engineering and AI integration.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with opportunities to collaborate on innovative projects.
- Why this job: Make an impact in the exciting field of AI and video technology.
- Qualifications: Experience in Python development and a passion for video engineering.
Overview
Joining V-Nova's Integration Team as a Software Engineer will give you the opportunity to work at the intersection of video engineering and artificial intelligence. You will help integrate V-Nova's video technologies multimodal workflows using Python to turn new ideas into practical, reliable systems.
The work will span offline video curation and large-scale dataset preparation through to real-time and cloud-based video inference. This will include building workflows, integrating codecs with AI and media frameworks, and exploring how LCEVC and VC-6 can reduce the amount of video data, decoding and processing required by AI applications.
The Integration Team's day-to-day work is dynamic. You will collaborate with codec engineers, AI specialists and external engineering teams, investigating unfamiliar systems and developing solutions that make V-Nova technology straightforward to evaluate and adopt. You are proactive, curious and comfortable contributing to wide-ranging technical discussions.
Responsibilities
- Develop and maintain production-quality Python integrations, tools and sample applications for V-Nova's LCEVC and VC-6 technologies within AI video workflows.
- Integrate codec SDKs into video curation, data preparation and inference pipelines, including workflows using technologies such as NVIDIA NeMo Curator, with either native integrations or via frameworks such as FFmpeg and GStreamer.
- Build and maintain video processing pipelines covering ingest, frame and clip extraction, transcoding, timestamps, keyframes, metadata and audio/video synchronisation.
- Connect video processing stages to computer-vision and multimodal AI models for tasks such as classification, detection, captioning, embeddings, retrieval and structured output generation.
- Prototype and benchmark codec-aware inference workflows, including the selective use of resolutions or regions of interest, and evaluate their impact on accuracy, latency, throughput, scalability and cost.
- Create automated tests, performance measurements and clear technical documentation that help colleagues, customers and partners reproduce and evaluate integrations.
- Collaborate with colleagues and external engineering teams to scope work, communicate progress and deliver integrations to production.
Qualifications
- Commercial software development experience using Python, including writing maintainable, tested and documented code.
- Practical video engineering knowledge and a basic understanding of how video streams work, including codecs and containers, frame extraction, timestamps, keyframes, audio/video synchronisation, transcoding and streaming fundamentals.
- Good problem-solving skills and confidence working across unfamiliar codebases, third-party libraries and APIs.
- Clear written and verbal communication, including concise progress updates and technical documentation.
- A degree in Computer Science, Engineering or a related discipline, or equivalent practical experience.
Desirable Experience:
- Experience with virtualisation and containerisation technologies, including Docker, and an understanding of building and managing portable, scalable environments.
- Experience working with AWS or similar services and deploying, managing or supporting applications in cloud-based environments.
- Experience with video curation or data preparation frameworks, or with building scalable batch and streaming data pipelines.
- Experience with multimodal AI, including LLM or VLM APIs, image and video understanding, embeddings, structured outputs, tool or function calling, and retrieval-augmented generation.
- Experience deploying and optimising AI inference workloads, with an understanding of performance considerations such as latency, throughput, scalability and cost.
- Direct development experience with FFmpeg or GStreamer.
- Experience with GPU-accelerated video or AI technologies such as CUDA, PyTorch, TensorRT, Triton Inference Server or NVIDIA DeepStream.
Integration Engineer - AI Pipelines in London employer: V-Nova
V-Nova is an exceptional employer that fosters a collaborative and innovative work culture, particularly for those passionate about the intersection of video engineering and artificial intelligence. As part of the Integration Team, you'll have the opportunity to work on cutting-edge technologies in a dynamic environment, with ample opportunities for professional growth and development. Located in a vibrant tech hub, V-Nova offers a supportive atmosphere where your contributions are valued, and you can make a meaningful impact on the future of video technology.
StudySmarter Expert Advice🤫
We think this is how you could land Integration Engineer - AI Pipelines in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at V-Nova or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to V-Nova.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like V-Nova.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like V-Nova that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Integration Engineer - AI Pipelines in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at V-Nova.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at V-Nova and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at V-Nova
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If V-Nova uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
