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About the Role

The Visual AI Analyst will join V-Nova's Strategic Analytics & Business Insights (SABI) team, working at the intersection of analytics, product development, and business development. This role will help translate V-Nova's hierarchical visual data technologies into measurable performance advantages and compelling customer propositions for Visual AI workflows. You will collaborate with Product, Engineering, Integration, and Commercial teams to develop, validate, and launch Visual AI acceleration solutions based on V-Nova technologies. The work is varied, involving analysis of GPU benchmark logs, building AI-assisted dashboards, assessing caption or embedding quality, researching AI frameworks, and translating technical results into business cases. We seek a high-learning-velocity analyst who thrives on unfamiliar problems, can structure ambiguity, works independently, and is driven by achieving useful results. Prior deep knowledge of video compression or Visual AI is not required; curiosity, analytical rigor, and rapid learning are paramount.

Responsibilities

Design, support, and analyze benchmarks and experiments across visual AI training and inference workflows, quantifying the impact of V-Nova technologies on quality, latency, throughput, compute, storage, and cost.
Transform raw test artifacts into insights, identify anomalies and bottlenecks, form hypotheses, and collaborate with engineering colleagues to validate root causes and optimization opportunities.
Build practical internal analytics tools, including dashboards, parsers, report generators, scripts, and automations, leveraging modern AI coding agents to enhance capabilities and improve experimentation speed and interpretability.
Collaborate with Product and Engineering to translate evidence into decisions, defining test plans and acceptance criteria, identifying optimal configurations, prioritizing follow-up work, and producing clear recommendations.
Support V-Nova's Visual AI go-to-market and business development through use-case and ecosystem research, competitor analysis, market sizing, pricing, and business-case work, converting technical evidence into concise partner and customer materials and integration priorities.
Collaborate with Marketing, other internal teams, and external partners to translate technical evidence into high-quality thought leadership and market-facing content, including blogs, articles, social media communications, scientific publications, and event materials.
Own the practical discipline of experiments and analysis, coordinating datasets and cloud GPU resources, ensuring reproducibility and clear documentation of results and artifacts, communicating progress effectively, and driving issues to resolution.

Requirements

A strong analytical and quantitative problem-solving mindset.
Comfortable transitioning from ambiguous questions to structured investigations, challenging illogical results, and following evidence to conclusions.
A Master's degree in a quantitatively rigorous discipline, or equivalent demonstrable experience, with hands-on comfort analyzing and visualizing data.
Working familiarity with at least one programming or scripting language (e.g., Python, R, or similar) for analytical problem-solving is strongly preferred.
An AI-native working style, actively using modern LLMs and AI agents for research, analysis, coding, prototyping, and documentation, and using them to acquire skills rapidly.
A strong growth and learning attitude, characterized by high curiosity, intellectual humility, willingness to seek feedback, and motivation to understand unfamiliar technical domains sufficiently to contribute meaningfully.
A can-do, get-stuff-done attitude with strong ownership and focus on outcomes.
Comfort operating with limited supervision, navigating imperfect information and changing priorities, and finding practical solutions to blockers.
Clear written and verbal communication in English, with attention to detail and experimental rigor.
Ability to explain quantitative and technical findings concisely to both technical and commercial stakeholders.
Ability to keep artifacts disciplined and reproducible.
A collaborative team attitude and the ability to work effectively in a diverse environment with colleagues and partners across different functions, technical backgrounds, and seniority levels.

Skills

Python
R
Modern LLMs
AI agents
Data analysis
Data visualization
Benchmarking
Experimental design
Performance analysis
AI coding tools
Linux
Docker
Cloud platforms
GPUs
NVIDIA tooling
AWS
Video processing
Image processing
FFmpeg
Codecs
Compression technologies
Technology strategy
Market research
Consulting-style analysis
Business cases
Customer-facing work
Partner-facing work
Computer vision
Multimodal AI
Vision-language models
Embeddings
Captioning
Retrieval
Data curation

Location

London

Work Type

Full-time

Experience Level

Mid-level

Education Level

Master's degree

About the Company

V-Nova is a London-based technology company specializing in visual data architectures for AI, media, and immersive applications.
Its hierarchical, compute-aware data formats structure and add intelligence to video, images, and point clouds, enabling systems to access and process only necessary visual information, reducing data movement, decoding, and compute in demanding visual workflows and improving the efficiency of large-scale AI processing.
V-Nova has contributed key intellectual property to internationally standardized technologies like MPEG-5 Part 2 LCEVC and SMPTE VC-6 (ST 2117), and develops PresenZ for volumetric and 6DoF experiences.
With a portfolio exceeding 1,600 international patents, V-Nova combines deep-science R&D with highly optimized software products and integrations, bringing its technology into real-world media, cloud, and AI systems.
The company is committed to the extraordinary, relying on talented, high-performing teams to solve complex problems and deliver on promises.
V-Nova's culture values individual empowerment, excellence, intellectual curiosity, and teamwork.
Across research, engineering, product, and commercial teams, V-Nova actively utilizes the latest AI tools to accelerate analysis, development, writing, and experimentation.
With groundbreaking technology, a fast-paced collaborative environment, and ambitious growth plans, this role offers an opportunity to make a visible contribution to an emerging category of Visual AI infrastructure.